---
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-male-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-male-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: 0.4348
- Wer: 0.3988

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 8.0084        | 0.5051  | 100  | 3.7458          | 0.9984 |
| 2.8136        | 1.0101  | 200  | 1.0029          | 0.7422 |
| 0.9647        | 1.5152  | 300  | 0.5870          | 0.5274 |
| 0.8539        | 2.0202  | 400  | 0.5461          | 0.5048 |
| 0.7525        | 2.5253  | 500  | 0.5256          | 0.4989 |
| 0.7307        | 3.0303  | 600  | 0.5101          | 0.4871 |
| 0.6997        | 3.5354  | 700  | 0.5032          | 0.4688 |
| 0.6882        | 4.0404  | 800  | 0.4879          | 0.4736 |
| 0.651         | 4.5455  | 900  | 0.4788          | 0.4559 |
| 0.6623        | 5.0505  | 1000 | 0.4799          | 0.4526 |
| 0.6339        | 5.5556  | 1100 | 0.4677          | 0.4419 |
| 0.6424        | 6.0606  | 1200 | 0.4650          | 0.4429 |
| 0.6365        | 6.5657  | 1300 | 0.4746          | 0.4462 |
| 0.556         | 7.0707  | 1400 | 0.4512          | 0.4381 |
| 0.5969        | 7.5758  | 1500 | 0.4597          | 0.4413 |
| 0.5772        | 8.0808  | 1600 | 0.4455          | 0.4284 |
| 0.5695        | 8.5859  | 1700 | 0.4565          | 0.4268 |
| 0.5752        | 9.0909  | 1800 | 0.4414          | 0.4187 |
| 0.5734        | 9.5960  | 1900 | 0.4450          | 0.4085 |
| 0.5465        | 10.1010 | 2000 | 0.4373          | 0.4155 |
| 0.5553        | 10.6061 | 2100 | 0.4520          | 0.4241 |
| 0.5289        | 11.1111 | 2200 | 0.4306          | 0.4085 |
| 0.5122        | 11.6162 | 2300 | 0.4372          | 0.4015 |
| 0.5659        | 12.1212 | 2400 | 0.4408          | 0.4010 |
| 0.5007        | 12.6263 | 2500 | 0.4274          | 0.3983 |
| 0.5366        | 13.1313 | 2600 | 0.4266          | 0.4026 |
| 0.5068        | 13.6364 | 2700 | 0.4366          | 0.3961 |
| 0.507         | 14.1414 | 2800 | 0.4359          | 0.3972 |
| 0.5031        | 14.6465 | 2900 | 0.4334          | 0.3967 |
| 0.4949        | 15.1515 | 3000 | 0.4348          | 0.3988 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0