File size: 2,159 Bytes
453f151 92d393b 453f151 92d393b 453f151 92d393b 453f151 490ac62 92d393b 453f151 92d393b 490ac62 453f151 ffd548f 92d393b 453f151 e75f1cc ffd548f 453f151 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_model
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. -->
# my_awesome_wnut_model
This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5795
- Precision: 0.2438
- Recall: 0.6759
- F1: 0.3583
- Accuracy: 0.8634
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.5943 | 1.0 | 38 | 0.3653 | 0.1156 | 0.6069 | 0.1943 | 0.8489 |
| 1.5943 | 2.0 | 76 | 0.3859 | 0.2032 | 0.7034 | 0.3153 | 0.8691 |
| 0.2445 | 3.0 | 114 | 0.4085 | 0.2422 | 0.8069 | 0.3726 | 0.8679 |
| 0.2445 | 4.0 | 152 | 0.3778 | 0.2013 | 0.6345 | 0.3056 | 0.8733 |
| 0.2445 | 5.0 | 190 | 0.4417 | 0.2010 | 0.5448 | 0.2937 | 0.8755 |
| 0.0861 | 6.0 | 228 | 0.5795 | 0.2438 | 0.6759 | 0.3583 | 0.8634 |
### Framework versions
- Transformers 4.53.2
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2
|