modelId
stringlengths 5
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| author
stringlengths 2
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| last_modified
timestamp[us, tz=UTC]date 2020-02-15 11:33:14
2025-09-11 06:30:11
| downloads
int64 0
223M
| likes
int64 0
11.7k
| library_name
stringclasses 555
values | tags
listlengths 1
4.05k
| pipeline_tag
stringclasses 55
values | createdAt
timestamp[us, tz=UTC]date 2022-03-02 23:29:04
2025-09-11 06:29:58
| card
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|---|---|---|---|---|---|---|---|---|---|
jonatasgrosman/exp_w2v2t_es_unispeech-ml_s952
|
jonatasgrosman
| 2022-07-11T12:05:40Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T12:04:48Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_unispeech-ml_s952
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_wavlm_s655
|
jonatasgrosman
| 2022-07-11T11:44:23Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T11:43:35Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_wavlm_s655
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
rajkumarrrk/t5-base-fine-tuned-on-cnn-dm
|
rajkumarrrk
| 2022-07-11T11:41:58Z | 5 | 0 |
transformers
|
[
"transformers",
"pytorch",
"t5",
"text2text-generation",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] |
text2text-generation
| 2022-07-11T10:48:43Z |
---
license: apache-2.0
---
T5-base fine-tuned on CNN/DM Summarization dataset.
Training args:
```
{
"learning_rate": 0.0001,
"logging_steps": 5000,
"lr_scheduler_type": "cosine",
"num_train_epochs": 2,
"per_device_train_batch_size": 16, # total batch size of 48
"save_total_limit": 1,
"weight_decay": 0.1
}
```
Generation kwargs:
```
{
"do_sample": true,
"max_new_tokens": 100,
"min_length": 50,
"temperature": 0.7,
"top_k": 0
},
````
Pre-processing: Append prompt with prefix "Summarize: "
Post-processing: None
Test split metrics:
```
{"lexical/meteor": 0.30857827917561603,
"lexical/rouge_rouge1": 0.41099971702474514,
"lexical/rouge_rouge2": 0.17676173608661166,
"lexical/rouge_rougeL": 0.2759112075051335,
"lexical/rouge_rougeLsum": 0.34316108028094616,
"lexical/bleu": 0.10747816852428271,
"semantic/bert_score": 0.8760301497472277}
```
|
jonatasgrosman/exp_w2v2t_es_wavlm_s26
|
jonatasgrosman
| 2022-07-11T11:37:51Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T11:37:01Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_wavlm_s26
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_wavlm_s115
|
jonatasgrosman
| 2022-07-11T11:30:30Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T11:29:51Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_wavlm_s115
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_no-pretraining_s953
|
jonatasgrosman
| 2022-07-11T11:23:40Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T11:22:50Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_no-pretraining_s953
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_no-pretraining_s807
|
jonatasgrosman
| 2022-07-11T11:18:11Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T11:17:31Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_no-pretraining_s807
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_vp-sv_s93
|
jonatasgrosman
| 2022-07-11T11:11:20Z | 5 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T11:10:33Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_vp-sv_s93
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_vp-sv_s44
|
jonatasgrosman
| 2022-07-11T11:07:51Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T11:07:05Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_vp-sv_s44
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_hubert_s456
|
jonatasgrosman
| 2022-07-11T10:56:25Z | 5 | 0 |
transformers
|
[
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:55:43Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_hubert_s456
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_unispeech_s461
|
jonatasgrosman
| 2022-07-11T10:49:40Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:49:09Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_unispeech_s461
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_unispeech_s990
|
jonatasgrosman
| 2022-07-11T10:43:19Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:42:38Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_unispeech_s990
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_xlsr-53_s103
|
jonatasgrosman
| 2022-07-11T10:40:01Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:39:11Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_xlsr-53_s103
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
GhostZen/distilbert-base-uncased-finetuned-squad
|
GhostZen
| 2022-07-11T10:38:10Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
question-answering
| 2022-07-11T10:09:04Z |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2t_es_xlsr-53_s756
|
jonatasgrosman
| 2022-07-11T10:35:54Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:35:16Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_xlsr-53_s756
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_xlsr-53_s377
|
jonatasgrosman
| 2022-07-11T10:32:41Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:32:11Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_xlsr-53_s377
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
wooihen/distilbert-base-uncased-finetuned-emotion
|
wooihen
| 2022-07-11T10:28:32Z | 7 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2022-07-11T10:04:15Z |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9225
- name: F1
type: f1
value: 0.922771245052197
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2146
- Accuracy: 0.9225
- F1: 0.9228
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8233 | 1.0 | 250 | 0.3068 | 0.9025 | 0.8995 |
| 0.2394 | 2.0 | 500 | 0.2146 | 0.9225 | 0.9228 |
### Framework versions
- Transformers 4.13.0
- Pytorch 1.11.0+cu113
- Datasets 1.16.1
- Tokenizers 0.10.3
|
AliMMZ/first_RL
|
AliMMZ
| 2022-07-11T10:26:59Z | 0 | 0 |
stable-baselines3
|
[
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] |
reinforcement-learning
| 2022-07-11T09:56:49Z |
---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- metrics:
- type: mean_reward
value: 265.62 +/- 14.05
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
---
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
```
|
jonatasgrosman/exp_w2v2t_es_vp-100k_s957
|
jonatasgrosman
| 2022-07-11T10:23:05Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:22:18Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_vp-100k_s957
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_es_wav2vec2_s596
|
jonatasgrosman
| 2022-07-11T10:16:07Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:15:16Z |
---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- es
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_es_wav2vec2_s596
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_vp-it_s975
|
jonatasgrosman
| 2022-07-11T10:03:48Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T10:03:23Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_vp-it_s975
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
fxmarty/20220711-h10m00s56_example_conll2003
|
fxmarty
| 2022-07-11T10:01:01Z | 0 | 0 | null |
[
"tensorboard",
"distilbert",
"token-classification",
"dataset:conll2003",
"region:us"
] |
token-classification
| 2022-07-11T10:00:56Z |
---
pipeline_tag: token-classification
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
tags:
- distilbert
---
**task**: `token-classification`
**Backend:** `sagemaker-training`
**Backend args:** `{'instance_type': 'ml.m5.2xlarge', 'supported_instructions': 'avx512'}`
**Number of evaluation samples:** `100`
Fixed parameters:
* **model_name_or_path**: `elastic/distilbert-base-uncased-finetuned-conll03-english`
* **dataset**:
* **path**: `conll2003`
* **eval_split**: `validation`
* **data_keys**: `{'primary': 'tokens'}`
* **ref_keys**: `['ner_tags']`
* **calibration_split**: `train`
* **node_exclusion**: `[]`
* **per_channel**: `False`
* **calibration**:
* **method**: `minmax`
* **num_calibration_samples**: `100`
* **framework**: `onnxruntime`
* **framework_args**:
* **opset**: `11`
* **optimization_level**: `1`
* **aware_training**: `False`
Benchmarked parameters:
* **quantization_approach**: `dynamic`, `static`
* **operators_to_quantize**: `['Add', 'MatMul']`, `['Add']`
# Evaluation
## Non-time metrics
| quantization_approach | operators_to_quantize | | precision (original) | precision (optimized) | | recall (original) | recall (optimized) | | f1 (original) | f1 (optimized) | | accuracy (original) | accuracy (optimized) |
| :-------------------: | :-------------------: | :-: | :------------------: | :-------------------: | :-: | :---------------: | :----------------: | :-: | :-----------: | :------------: | :-: | :-----------------: | :------------------: |
| `dynamic` | `['Add', 'MatMul']` | \| | 0.974 | 0.974 | \| | 0.955 | 0.949 | \| | 0.964 | 0.962 | \| | 0.990 | 0.989 |
| `dynamic` | `['Add']` | \| | 0.974 | 0.974 | \| | 0.955 | 0.955 | \| | 0.964 | 0.964 | \| | 0.990 | 0.990 |
| `static` | `['Add', 'MatMul']` | \| | 0.974 | 0.081 | \| | 0.955 | 0.222 | \| | 0.964 | 0.118 | \| | 0.990 | 0.467 |
| `static` | `['Add']` | \| | 0.974 | 0.073 | \| | 0.955 | 0.182 | \| | 0.964 | 0.105 | \| | 0.990 | 0.290 |
## Time metrics
Time benchmarks were run for 3 seconds per config.
Below, time metrics for batch size = 1, input length = 64.
| quantization_approach | operators_to_quantize | | latency_mean (original, ms) | latency_mean (optimized, ms) | | throughput (original, /s) | throughput (optimized, /s) |
| :-------------------: | :-------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: |
| `dynamic` | `['Add', 'MatMul']` | \| | 59.35 | 21.91 | \| | 17.00 | 45.67 |
| `dynamic` | `['Add']` | \| | 59.18 | 29.24 | \| | 17.00 | 34.33 |
| `static` | `['Add', 'MatMul']` | \| | 59.25 | 28.31 | \| | 17.00 | 35.33 |
| `static` | `['Add']` | \| | 58.77 | 31.80 | \| | 17.33 | 31.67 |
|
jonatasgrosman/exp_w2v2t_ru_vp-it_s817
|
jonatasgrosman
| 2022-07-11T09:59:54Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:59:26Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_vp-it_s817
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_r-wav2vec2_s408
|
jonatasgrosman
| 2022-07-11T09:53:37Z | 5 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:53:13Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_r-wav2vec2_s408
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_r-wav2vec2_s399
|
jonatasgrosman
| 2022-07-11T09:50:40Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:49:58Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_r-wav2vec2_s399
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
fxmarty/20220711-h09m49s39_example_conll2003
|
fxmarty
| 2022-07-11T09:49:44Z | 0 | 0 | null |
[
"tensorboard",
"distilbert",
"token-classification",
"dataset:conll2003",
"region:us"
] |
token-classification
| 2022-07-11T09:49:39Z |
---
pipeline_tag: token-classification
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
tags:
- distilbert
---
**task**: `token-classification`
**Backend:** `sagemaker-training`
**Backend args:** `{'instance_type': 'ml.m5.2xlarge', 'supported_instructions': 'avx512'}`
**Number of evaluation samples:** `10`
Fixed parameters:
* **model_name_or_path**: `elastic/distilbert-base-uncased-finetuned-conll03-english`
* **dataset**:
* **path**: `conll2003`
* **eval_split**: `validation`
* **data_keys**: `{'primary': 'tokens'}`
* **ref_keys**: `['ner_tags']`
* **calibration_split**: `train`
* **node_exclusion**: `[]`
* **per_channel**: `False`
* **calibration**:
* **method**: `minmax`
* **num_calibration_samples**: `100`
* **framework**: `onnxruntime`
* **framework_args**:
* **opset**: `11`
* **optimization_level**: `1`
* **aware_training**: `False`
Benchmarked parameters:
* **quantization_approach**: `dynamic`, `static`
* **operators_to_quantize**: `['Add', 'MatMul']`, `['Add']`
# Evaluation
## Non-time metrics
| quantization_approach | operators_to_quantize | | precision (original) | precision (optimized) | | recall (original) | recall (optimized) | | f1 (original) | f1 (optimized) | | accuracy (original) | accuracy (optimized) |
| :-------------------: | :-------------------: | :-: | :------------------: | :-------------------: | :-: | :---------------: | :----------------: | :-: | :-----------: | :------------: | :-: | :-----------------: | :------------------: |
| `dynamic` | `['Add', 'MatMul']` | \| | 0.970 | 0.969 | \| | 0.970 | 0.939 | \| | 0.970 | 0.954 | \| | 0.993 | 0.990 |
| `dynamic` | `['Add']` | \| | 0.970 | 0.970 | \| | 0.970 | 0.970 | \| | 0.970 | 0.970 | \| | 0.993 | 0.993 |
| `static` | `['Add', 'MatMul']` | \| | 0.970 | 0.104 | \| | 0.970 | 0.212 | \| | 0.970 | 0.140 | \| | 0.993 | 0.691 |
| `static` | `['Add']` | \| | 0.970 | 0.037 | \| | 0.970 | 0.121 | \| | 0.970 | 0.057 | \| | 0.993 | 0.110 |
## Time metrics
Time benchmarks were run for 3 seconds per config.
Below, time metrics for batch size = 1, input length = 64.
| quantization_approach | operators_to_quantize | | latency_mean (original, ms) | latency_mean (optimized, ms) | | throughput (original, /s) | throughput (optimized, /s) |
| :-------------------: | :-------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: |
| `dynamic` | `['Add', 'MatMul']` | \| | 60.12 | 18.13 | \| | 16.67 | 55.33 |
| `dynamic` | `['Add']` | \| | 59.49 | 29.12 | \| | 17.00 | 34.67 |
| `static` | `['Add', 'MatMul']` | \| | 58.89 | 24.30 | \| | 17.00 | 41.33 |
| `static` | `['Add']` | \| | 43.19 | 38.12 | \| | 23.33 | 26.33 |
|
jonatasgrosman/exp_w2v2t_ru_xls-r_s946
|
jonatasgrosman
| 2022-07-11T09:47:04Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:46:39Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_xls-r_s946
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_xls-r_s635
|
jonatasgrosman
| 2022-07-11T09:42:39Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:42:14Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_xls-r_s635
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_unispeech-sat_s418
|
jonatasgrosman
| 2022-07-11T09:26:37Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:26:11Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_unispeech-sat_s418
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_unispeech-sat_s423
|
jonatasgrosman
| 2022-07-11T09:23:21Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:22:56Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_unispeech-sat_s423
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_vp-nl_s131
|
jonatasgrosman
| 2022-07-11T09:17:04Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:16:37Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_vp-nl_s131
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_vp-nl_s328
|
jonatasgrosman
| 2022-07-11T09:14:06Z | 5 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:13:23Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_vp-nl_s328
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_vp-fr_s805
|
jonatasgrosman
| 2022-07-11T09:01:30Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T09:01:05Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_vp-fr_s805
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_unispeech-ml_s569
|
jonatasgrosman
| 2022-07-11T08:48:36Z | 5 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T08:48:11Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_unispeech-ml_s569
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_unispeech-ml_s947
|
jonatasgrosman
| 2022-07-11T08:45:37Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T08:44:54Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_unispeech-ml_s947
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_wavlm_s363
|
jonatasgrosman
| 2022-07-11T08:36:26Z | 3 | 1 |
transformers
|
[
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T08:36:00Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_wavlm_s363
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
ybelkada/japanese-dummy-tokenizer
|
ybelkada
| 2022-07-11T08:24:32Z | 4 | 1 |
transformers
|
[
"transformers",
"ja",
"japanese",
"tokenizer",
"en",
"dataset:snow_simplified_japanese_corpus",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-04-06T12:31:37Z |
---
language:
- en
- ja
license: mit
datasets:
- snow_simplified_japanese_corpus
tags:
- ja
- japanese
- tokenizer
widget:
- text: "誰が一番に着くか私には分かりません。"
---
# Japanese Dummy Tokenizer
Repository containing a dummy Japanese Tokenizer trained on ```snow_simplified_japanese_corpus``` dataset. The tokenizer has been trained using Hugging Face datasets in a streaming manner.
## Intended uses & limitations
You can use this tokenizer to tokenize Japanese sentences.
## How to use it
```
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("ybelkada/japanese-dummy-tokenizer")
```
## How to train the tokenizer
Check the file ```tokenizer.py```, you can freely adapt it to other datasets. This tokenizer is based on the tokenizer from ```csebuetnlp/mT5_multilingual_XLSum```.
|
jonatasgrosman/exp_w2v2t_ru_vp-sv_s658
|
jonatasgrosman
| 2022-07-11T08:21:28Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T08:20:56Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_vp-sv_s658
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_vp-sv_s772
|
jonatasgrosman
| 2022-07-11T08:18:26Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T08:17:19Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_vp-sv_s772
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_unispeech_s42
|
jonatasgrosman
| 2022-07-11T07:55:21Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:54:56Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_unispeech_s42
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_xlsr-53_s911
|
jonatasgrosman
| 2022-07-11T07:52:25Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:51:37Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_xlsr-53_s911
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_xlsr-53_s303
|
jonatasgrosman
| 2022-07-11T07:45:29Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:44:48Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_xlsr-53_s303
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_ru_vp-100k_s69
|
jonatasgrosman
| 2022-07-11T07:35:45Z | 5 | 1 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:35:04Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_vp-100k_s69
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
osanseviero/tfjs-mobilenet-611
|
osanseviero
| 2022-07-11T07:33:29Z | 0 | 0 | null |
[
"image-classification",
"tfjs",
"license:mit",
"region:us"
] |
image-classification
| 2022-07-11T07:33:21Z |
---
license: mit
tags:
- image-classification
- tfjs
---
## TensorFlow.js version of Mobilenet
Pushed from Web
|
jonatasgrosman/exp_w2v2t_ru_wav2vec2_s847
|
jonatasgrosman
| 2022-07-11T07:28:38Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:28:07Z |
---
language:
- ru
license: apache-2.0
tags:
- automatic-speech-recognition
- ru
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_ru_wav2vec2_s847
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-it_s449
|
jonatasgrosman
| 2022-07-11T07:20:08Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:19:25Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-it_s449
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-it_s149
|
jonatasgrosman
| 2022-07-11T07:16:32Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:15:48Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-it_s149
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_r-wav2vec2_s925
|
jonatasgrosman
| 2022-07-11T07:09:56Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:09:27Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_r-wav2vec2_s925
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_r-wav2vec2_s170
|
jonatasgrosman
| 2022-07-11T07:01:02Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T07:00:22Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_r-wav2vec2_s170
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
hellennamulinda/eng-lug
|
hellennamulinda
| 2022-07-11T06:45:00Z | 10 | 0 |
transformers
|
[
"transformers",
"pytorch",
"marian",
"text2text-generation",
"autotrain",
"unk",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text2text-generation
| 2022-07-01T13:10:28Z |
---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
co2_eq_emissions: 0.04087910671538076
---
# Model Trained Using AutoTrain
- Problem type: Translation
- Model ID: 1026034854
- CO2 Emissions (in grams): 0.04087910671538076
## Validation Metrics
- Loss: 1.0871405601501465
- Rouge1: 55.8225
- Rouge2: 34.1547
- RougeL: 54.4274
- RougeLsum: 54.408
- Gen Len: 23.178
## Usage
You can use cURL to access this model:
```
$ curl -X POST -H "Authorization: Bearer YOUR_HUGGINGFACE_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/hellennamulinda/autotrain-eng-lug-1070637495
```
|
jonatasgrosman/exp_w2v2t_nl_vp-nl_s747
|
jonatasgrosman
| 2022-07-11T06:29:19Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T06:28:49Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-nl_s747
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-nl_s424
|
jonatasgrosman
| 2022-07-11T06:23:18Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T06:22:52Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-nl_s424
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-es_s476
|
jonatasgrosman
| 2022-07-11T06:20:15Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T06:19:49Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-es_s476
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-es_s496
|
jonatasgrosman
| 2022-07-11T06:14:20Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T06:13:55Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-es_s496
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-fr_s417
|
jonatasgrosman
| 2022-07-11T06:08:16Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T06:07:50Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-fr_s417
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_wavlm_s246
|
jonatasgrosman
| 2022-07-11T05:52:32Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T05:51:59Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_wavlm_s246
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
AndyChiang/bert-test
|
AndyChiang
| 2022-07-11T05:50:10Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tf",
"bert",
"fill-mask",
"generated_from_keras_callback",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
fill-mask
| 2022-07-11T03:34:14Z |
---
tags:
- generated_from_keras_callback
model-index:
- name: bert-test
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# bert-test
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
### Training results
### Framework versions
- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2t_nl_no-pretraining_s512
|
jonatasgrosman
| 2022-07-11T05:43:20Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T05:42:54Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_no-pretraining_s512
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_no-pretraining_s399
|
jonatasgrosman
| 2022-07-11T05:40:21Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T05:39:37Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_no-pretraining_s399
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-sv_s510
|
jonatasgrosman
| 2022-07-11T05:34:04Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T05:33:38Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-sv_s510
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-sv_s607
|
jonatasgrosman
| 2022-07-11T05:27:33Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T05:27:07Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-sv_s607
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_hubert_s562
|
jonatasgrosman
| 2022-07-11T05:00:40Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T05:00:15Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_hubert_s562
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_hubert_s319
|
jonatasgrosman
| 2022-07-11T04:36:03Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T04:35:38Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_hubert_s319
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_unispeech_s683
|
jonatasgrosman
| 2022-07-11T04:24:15Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T04:23:30Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_unispeech_s683
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_unispeech_s853
|
jonatasgrosman
| 2022-07-11T04:05:42Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T04:05:02Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_unispeech_s853
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_xlsr-53_s948
|
jonatasgrosman
| 2022-07-11T03:52:19Z | 6 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T03:51:53Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_xlsr-53_s948
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
infinitejoy/MLAgents-Worm
|
infinitejoy
| 2022-07-11T03:50:39Z | 14 | 0 |
ml-agents
|
[
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Worm",
"region:us"
] |
reinforcement-learning
| 2022-07-11T03:50:32Z |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Worm
library_name: ml-agents
---
# **ppo** Agent playing **Worm**
This is a trained model of a **ppo** agent playing **Worm** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the training
```
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
```
### Watch your Agent play
You can watch your agent **playing directly in your browser:**.
1. Go to https://huggingface.co/spaces/unity/ML-Agents-Worm
2. Step 1: Write your model_id: infinitejoy/MLAgents-Worm
3. Step 2: Select your *.nn /*.onnx file
4. Click on Watch the agent play 👀
|
jonatasgrosman/exp_w2v2t_nl_xlsr-53_s972
|
jonatasgrosman
| 2022-07-11T03:31:44Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T03:31:17Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_xlsr-53_s972
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_vp-100k_s899
|
jonatasgrosman
| 2022-07-11T03:12:37Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T03:11:52Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_vp-100k_s899
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
Lvxue/finetuned-mbart-large-10epoch
|
Lvxue
| 2022-07-11T03:11:38Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"generated_from_trainer",
"en",
"ro",
"dataset:wmt16",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text2text-generation
| 2022-07-08T07:40:58Z |
---
language:
- en
- ro
tags:
- generated_from_trainer
datasets:
- wmt16
model-index:
- name: finetuned-mbart-large-10epoch
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetuned-mbart-large-10epoch
This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on the wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6032
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
### Training results
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2t_nl_wav2vec2_s721
|
jonatasgrosman
| 2022-07-11T03:04:17Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T03:03:52Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_wav2vec2_s721
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_wav2vec2_s754
|
jonatasgrosman
| 2022-07-11T02:56:30Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T02:56:05Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_wav2vec2_s754
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_nl_wav2vec2_s379
|
jonatasgrosman
| 2022-07-11T02:46:55Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"nl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T02:46:29Z |
---
language:
- nl
license: apache-2.0
tags:
- automatic-speech-recognition
- nl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_nl_wav2vec2_s379
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (nl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_vp-it_s992
|
jonatasgrosman
| 2022-07-11T02:32:42Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T02:32:18Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_vp-it_s992
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_xls-r_s662
|
jonatasgrosman
| 2022-07-11T01:42:16Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T01:41:33Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_xls-r_s662
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_unispeech-sat_s108
|
jonatasgrosman
| 2022-07-11T01:09:54Z | 6 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T01:09:13Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_unispeech-sat_s108
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_unispeech-sat_s364
|
jonatasgrosman
| 2022-07-11T01:00:50Z | 5 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T01:00:06Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_unispeech-sat_s364
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_vp-nl_s354
|
jonatasgrosman
| 2022-07-11T00:31:29Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T00:31:05Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_vp-nl_s354
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_vp-es_s803
|
jonatasgrosman
| 2022-07-11T00:20:03Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-11T00:19:20Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_vp-es_s803
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_unispeech-ml_s545
|
jonatasgrosman
| 2022-07-10T23:44:50Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T23:44:05Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_unispeech-ml_s545
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_unispeech-ml_s527
|
jonatasgrosman
| 2022-07-10T23:36:00Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T23:35:36Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_unispeech-ml_s527
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_unispeech-ml_s779
|
jonatasgrosman
| 2022-07-10T23:31:09Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T23:30:26Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_unispeech-ml_s779
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_wavlm_s887
|
jonatasgrosman
| 2022-07-10T23:17:52Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T23:17:06Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_wavlm_s887
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_wavlm_s753
|
jonatasgrosman
| 2022-07-10T23:09:20Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T23:08:50Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_wavlm_s753
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_vp-sv_s953
|
jonatasgrosman
| 2022-07-10T22:47:21Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T22:46:56Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_vp-sv_s953
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_hubert_s390
|
jonatasgrosman
| 2022-07-10T22:44:26Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T22:44:02Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_hubert_s390
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_hubert_s507
|
jonatasgrosman
| 2022-07-10T22:41:25Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T22:40:39Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_hubert_s507
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
malinoori/wav2vec2-base-2
|
malinoori
| 2022-07-10T22:33:08Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T20:17:40Z |
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-2
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5953
- eval_wer: 0.3621
- eval_runtime: 54.4895
- eval_samples_per_second: 30.832
- eval_steps_per_second: 3.854
- epoch: 22.61
- step: 22500
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2t_et_unispeech_s605
|
jonatasgrosman
| 2022-07-10T22:28:55Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T22:28:31Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_unispeech_s605
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_xlsr-53_s186
|
jonatasgrosman
| 2022-07-10T22:25:50Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T22:25:17Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_xlsr-53_s186
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_xlsr-53_s952
|
jonatasgrosman
| 2022-07-10T22:14:42Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T22:14:16Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_xlsr-53_s952
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_xlsr-53_s474
|
jonatasgrosman
| 2022-07-10T22:11:50Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T22:11:24Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_xlsr-53_s474
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_vp-100k_s377
|
jonatasgrosman
| 2022-07-10T21:58:55Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T21:58:31Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_vp-100k_s377
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
nestoralvaro/distilbert-base-uncased-finetuned-ner
|
nestoralvaro
| 2022-07-10T21:28:55Z | 4 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
token-classification
| 2022-07-10T15:30:09Z |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4253
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9226
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log | 1.0 | 15 | 0.4677 | 0.0 | 0.0 | 0.0 | 0.9226 |
| No log | 2.0 | 30 | 0.4303 | 0.0 | 0.0 | 0.0 | 0.9226 |
| No log | 3.0 | 45 | 0.4253 | 0.0 | 0.0 | 0.0 | 0.9226 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2t_et_vp-100k_s756
|
jonatasgrosman
| 2022-07-10T21:23:08Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T21:22:43Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_vp-100k_s756
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_vp-100k_s103
|
jonatasgrosman
| 2022-07-10T20:58:08Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T20:57:43Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_vp-100k_s103
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
elonmuskceo/tfjs-mobilenet-yay
|
elonmuskceo
| 2022-07-10T20:57:54Z | 0 | 0 | null |
[
"image-classification",
"tfjs",
"license:mit",
"region:us"
] |
image-classification
| 2022-07-10T20:57:46Z |
---
license: mit
tags:
- image-classification
- tfjs
---
## TensorFlow.js version of Mobilenet
Pushed from Web
|
jonatasgrosman/exp_w2v2t_et_wav2vec2_s253
|
jonatasgrosman
| 2022-07-10T20:52:12Z | 5 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T20:51:49Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_wav2vec2_s253
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_et_wav2vec2_s112
|
jonatasgrosman
| 2022-07-10T20:49:17Z | 3 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"et",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T20:48:53Z |
---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- et
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_et_wav2vec2_s112
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (et)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_pl_vp-it_s157
|
jonatasgrosman
| 2022-07-10T20:42:40Z | 8 | 0 |
transformers
|
[
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pl",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] |
automatic-speech-recognition
| 2022-07-10T20:42:16Z |
---
language:
- pl
license: apache-2.0
tags:
- automatic-speech-recognition
- pl
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_pl_vp-it_s157
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pl)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
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