---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: tun_msa_wav2vec2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# tun_msa_wav2vec2

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5373
- Wer: 0.5598
- Cer: 0.1779

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 4.1696        | 2.2727  | 700   | 1.2685          | 0.8366 | 0.3108 |
| 1.4028        | 4.5455  | 1400  | 0.7872          | 0.7136 | 0.2375 |
| 1.0872        | 6.8182  | 2100  | 0.6787          | 0.6778 | 0.2198 |
| 0.9573        | 9.0909  | 2800  | 0.6569          | 0.6605 | 0.2121 |
| 0.939         | 11.3636 | 3500  | 0.6115          | 0.6409 | 0.2040 |
| 0.8378        | 13.6364 | 4200  | 0.6097          | 0.6288 | 0.2000 |
| 0.8026        | 15.9091 | 4900  | 0.5843          | 0.6125 | 0.1949 |
| 0.7712        | 18.1818 | 5600  | 0.5830          | 0.6080 | 0.1942 |
| 0.7561        | 20.4545 | 6300  | 0.5637          | 0.5951 | 0.1889 |
| 0.7255        | 22.7273 | 7000  | 0.5630          | 0.5888 | 0.1869 |
| 0.7051        | 25.0    | 7700  | 0.5573          | 0.5852 | 0.1848 |
| 0.6873        | 27.2727 | 8400  | 0.5577          | 0.5799 | 0.1841 |
| 0.6722        | 29.5455 | 9100  | 0.5460          | 0.5748 | 0.1827 |
| 0.6673        | 31.8182 | 9800  | 0.5495          | 0.5725 | 0.1827 |
| 0.6359        | 34.0909 | 10500 | 0.5509          | 0.5720 | 0.1831 |
| 0.6513        | 36.3636 | 11200 | 0.5455          | 0.5676 | 0.1804 |
| 0.6402        | 38.6364 | 11900 | 0.5373          | 0.5649 | 0.1797 |
| 0.6302        | 40.9091 | 12600 | 0.5399          | 0.5643 | 0.1797 |
| 0.617         | 43.1818 | 13300 | 0.5368          | 0.5628 | 0.1793 |
| 0.6353        | 45.4545 | 14000 | 0.5369          | 0.5596 | 0.1786 |
| 0.6277        | 47.7273 | 14700 | 0.5361          | 0.5597 | 0.1783 |
| 0.5956        | 50.0    | 15400 | 0.5373          | 0.5598 | 0.1779 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1