---
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: 0.3234
- Wer: 0.3755

## 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: 2500.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 14.2297       | 0.8850  | 100  | 3.4836          | 1.0056 |
| 4.1389        | 1.7699  | 200  | 0.5562          | 0.5694 |
| 1.3643        | 2.6549  | 300  | 0.4360          | 0.4958 |
| 1.1715        | 3.5398  | 400  | 0.3980          | 0.4824 |
| 1.1309        | 4.4248  | 500  | 0.3785          | 0.4583 |
| 1.0283        | 5.3097  | 600  | 0.3741          | 0.4477 |
| 1.0148        | 6.1947  | 700  | 0.3669          | 0.4403 |
| 0.9961        | 7.0796  | 800  | 0.3607          | 0.4356 |
| 0.9248        | 7.9646  | 900  | 0.3581          | 0.4236 |
| 0.9482        | 8.8496  | 1000 | 0.3463          | 0.4356 |
| 0.8815        | 9.7345  | 1100 | 0.3488          | 0.4273 |
| 0.8209        | 10.6195 | 1200 | 0.3384          | 0.4    |
| 0.8754        | 11.5044 | 1300 | 0.3459          | 0.4051 |
| 0.8454        | 12.3894 | 1400 | 0.3317          | 0.3884 |
| 0.8164        | 13.2743 | 1500 | 0.3319          | 0.4032 |
| 0.7673        | 14.1593 | 1600 | 0.3311          | 0.3921 |
| 0.7953        | 15.0442 | 1700 | 0.3333          | 0.3944 |
| 0.7527        | 15.9292 | 1800 | 0.3313          | 0.3917 |
| 0.763         | 16.8142 | 1900 | 0.3278          | 0.3931 |
| 0.7319        | 17.6991 | 2000 | 0.3234          | 0.3755 |
| 0.7352        | 18.5841 | 2100 | 0.3248          | 0.3806 |
| 0.7017        | 19.4690 | 2200 | 0.3334          | 0.3852 |
| 0.6902        | 20.3540 | 2300 | 0.3304          | 0.3889 |
| 0.707         | 21.2389 | 2400 | 0.3314          | 0.3856 |


### Framework versions

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