|
--- |
|
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-balanced-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-balanced-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: 0.3740 |
|
- Wer: 0.3990 |
|
|
|
## 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 |
|
- 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 | |
|
|:-------------:|:-------:|:----:|:---------------:|:------:| |
|
| 7.7726 | 0.4464 | 100 | 3.8109 | 0.9938 | |
|
| 2.5726 | 0.8929 | 200 | 0.8106 | 0.6167 | |
|
| 0.7986 | 1.3393 | 300 | 0.5409 | 0.5258 | |
|
| 0.6324 | 1.7857 | 400 | 0.5256 | 0.5054 | |
|
| 0.603 | 2.2321 | 500 | 0.4854 | 0.4832 | |
|
| 0.59 | 2.6786 | 600 | 0.4733 | 0.4846 | |
|
| 0.5489 | 3.125 | 700 | 0.4440 | 0.4657 | |
|
| 0.5173 | 3.5714 | 800 | 0.4322 | 0.4576 | |
|
| 0.5315 | 4.0179 | 900 | 0.4286 | 0.4453 | |
|
| 0.4912 | 4.4643 | 1000 | 0.4254 | 0.4458 | |
|
| 0.4728 | 4.9107 | 1100 | 0.4346 | 0.4430 | |
|
| 0.4989 | 5.3571 | 1200 | 0.4050 | 0.4292 | |
|
| 0.4661 | 5.8036 | 1300 | 0.4019 | 0.4255 | |
|
| 0.4755 | 6.25 | 1400 | 0.4129 | 0.4449 | |
|
| 0.4603 | 6.6964 | 1500 | 0.4046 | 0.4255 | |
|
| 0.4229 | 7.1429 | 1600 | 0.3939 | 0.4150 | |
|
| 0.455 | 7.5893 | 1700 | 0.4133 | 0.4155 | |
|
| 0.4501 | 8.0357 | 1800 | 0.3978 | 0.4065 | |
|
| 0.45 | 8.4821 | 1900 | 0.3925 | 0.4231 | |
|
| 0.4226 | 8.9286 | 2000 | 0.3901 | 0.4098 | |
|
| 0.3973 | 9.375 | 2100 | 0.3810 | 0.4056 | |
|
| 0.4038 | 9.8214 | 2200 | 0.4178 | 0.4117 | |
|
| 0.4559 | 10.2679 | 2300 | 0.3875 | 0.4075 | |
|
| 0.4399 | 10.7143 | 2400 | 0.3742 | 0.3990 | |
|
| 0.3545 | 11.1607 | 2500 | 0.3818 | 0.4013 | |
|
| 0.4452 | 11.6071 | 2600 | 0.3906 | 0.3980 | |
|
| 0.4014 | 12.0536 | 2700 | 0.3752 | 0.3999 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu124 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
