---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-MGB3
  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-MGB3

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5770
- Wer: 99.9986

## 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: 1e-05
- train_batch_size: 14
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 8.1649        | 0.83  | 250  | 8.8182          | 100.0211 |
| 4.4764        | 1.66  | 500  | 5.1784          | 100.0254 |
| 3.962         | 2.48  | 750  | 4.6853          | 100.0310 |
| 3.7546        | 3.31  | 1000 | 4.4820          | 101.1220 |
| 3.5712        | 4.14  | 1250 | 4.3419          | 101.5181 |
| 5.9242        | 4.97  | 1500 | 4.2276          | 100.0    |
| 6.072         | 5.79  | 1750 | 4.1441          | 100.0    |
| 3.3164        | 6.62  | 2000 | 4.0701          | 100.0    |
| 3.2964        | 7.45  | 2250 | 3.9941          | 100.0    |
| 3.2501        | 8.28  | 2500 | 3.9978          | 100.0    |
| 3.2477        | 9.11  | 2750 | 3.9468          | 100.0    |
| 3.9197        | 9.93  | 3000 | 3.9109          | 100.0    |
| 3.1928        | 10.76 | 3250 | 3.8802          | 100.0    |
| 3.182         | 11.59 | 3500 | 3.8802          | 100.0    |
| 3.181         | 12.42 | 3750 | 3.7959          | 100.0    |
| 4.3975        | 13.25 | 4000 | 3.8292          | 100.0    |
| 3.8885        | 14.07 | 4250 | 3.7765          | 100.0    |
| 4.2643        | 14.9  | 4500 | 3.7765          | 100.0    |
| 3.1381        | 15.73 | 4750 | 3.7338          | 100.0    |
| 3.1197        | 16.56 | 5000 | 3.7391          | 100.0    |
| 3.1345        | 17.38 | 5250 | 3.7267          | 100.0    |
| 4.4275        | 18.21 | 5500 | 3.7405          | 100.0    |
| 4.3669        | 19.04 | 5750 | 3.7220          | 100.0    |
| 3.1225        | 19.87 | 6000 | 3.7093          | 99.9915  |
| 3.8043        | 20.7  | 6250 | 3.6449          | 99.9958  |
| 3.8089        | 21.52 | 6500 | 3.6988          | 100.0    |
| 4.2457        | 22.35 | 6750 | 3.6125          | 100.0    |
| 3.0956        | 23.18 | 7000 | 3.6309          | 99.9972  |
| 3.1013        | 24.01 | 7250 | 3.5845          | 99.9930  |
| 5.8493        | 24.83 | 7500 | 3.5770          | 99.9986  |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1
- Datasets 2.19.1
- Tokenizers 0.13.3