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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- toigen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-toigen-baseline-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. -->
# mms-1b-toigen-baseline-model
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the TOIGEN - TOI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2843
- Wer: 0.3621
## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use 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: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 13.6402 | 0.8163 | 100 | 3.4942 | 1.0229 |
| 3.8366 | 1.6286 | 200 | 0.5119 | 0.5733 |
| 1.0697 | 2.4408 | 300 | 0.3992 | 0.5292 |
| 0.8653 | 3.2531 | 400 | 0.3590 | 0.4804 |
| 0.8315 | 4.0653 | 500 | 0.3377 | 0.4521 |
| 0.7544 | 4.8816 | 600 | 0.3275 | 0.4396 |
| 0.7324 | 5.6939 | 700 | 0.3208 | 0.4233 |
| 0.6181 | 6.5061 | 800 | 0.3130 | 0.4154 |
| 0.7027 | 7.3184 | 900 | 0.3070 | 0.4075 |
| 0.6316 | 8.1306 | 1000 | 0.3032 | 0.4046 |
| 0.6276 | 8.9469 | 1100 | 0.2943 | 0.4037 |
| 0.6312 | 9.7592 | 1200 | 0.2938 | 0.4042 |
| 0.5482 | 10.5714 | 1300 | 0.2933 | 0.4004 |
| 0.5582 | 11.3837 | 1400 | 0.2979 | 0.3946 |
| 0.594 | 12.1959 | 1500 | 0.2907 | 0.3904 |
| 0.5565 | 13.0082 | 1600 | 0.2973 | 0.3912 |
| 0.5375 | 13.8245 | 1700 | 0.2907 | 0.385 |
| 0.5488 | 14.6367 | 1800 | 0.2880 | 0.3842 |
| 0.5245 | 15.4490 | 1900 | 0.2902 | 0.3833 |
| 0.524 | 16.2612 | 2000 | 0.2874 | 0.3692 |
| 0.5159 | 17.0735 | 2100 | 0.2849 | 0.3767 |
| 0.4802 | 17.8898 | 2200 | 0.2927 | 0.3738 |
| 0.481 | 18.7020 | 2300 | 0.2876 | 0.3792 |
| 0.5105 | 19.5143 | 2400 | 0.2842 | 0.3754 |
| 0.5144 | 20.3265 | 2500 | 0.2845 | 0.3692 |
| 0.4674 | 21.1388 | 2600 | 0.2840 | 0.3658 |
| 0.4604 | 21.9551 | 2700 | 0.2855 | 0.37 |
| 0.4823 | 22.7673 | 2800 | 0.2852 | 0.3717 |
| 0.4502 | 23.5796 | 2900 | 0.2833 | 0.3708 |
| 0.4545 | 24.3918 | 3000 | 0.2825 | 0.3717 |
| 0.4799 | 25.2041 | 3100 | 0.2825 | 0.3638 |
| 0.4552 | 26.0163 | 3200 | 0.2848 | 0.3679 |
| 0.4415 | 26.8327 | 3300 | 0.2843 | 0.3625 |
| 0.4331 | 27.6449 | 3400 | 0.2850 | 0.3613 |
| 0.4373 | 28.4571 | 3500 | 0.2843 | 0.3617 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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