---
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