---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: tun_wav2vec8
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/myriam-charfeddine5/huggingface/runs/w8fp109b)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/myriam-charfeddine5/huggingface/runs/w8fp109b)
# tun_wav2vec8

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2858
- Wer: 0.5831
- Cer: 0.1539

## 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: 0.0001
- train_batch_size: 10
- 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: 80
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 2.2416        | 5.0   | 300  | 1.6570          | 0.9561 | 0.3341 |
| 0.6397        | 10.0  | 600  | 1.0742          | 0.8652 | 0.3005 |
| 0.4434        | 15.0  | 900  | 1.2856          | 0.7743 | 0.2411 |
| 0.3084        | 20.0  | 1200 | 1.0868          | 0.7335 | 0.2106 |
| 0.2708        | 25.0  | 1500 | 0.9412          | 0.7367 | 0.1960 |
| 0.2519        | 30.0  | 1800 | 0.8857          | 0.6959 | 0.1863 |
| 0.1833        | 35.0  | 2100 | 1.2220          | 0.6740 | 0.1856 |
| 0.1354        | 40.0  | 2400 | 1.1682          | 0.6520 | 0.1786 |
| 0.1363        | 45.0  | 2700 | 1.1745          | 0.6865 | 0.1794 |
| 0.129         | 50.0  | 3000 | 1.0153          | 0.6426 | 0.1736 |
| 0.1036        | 55.0  | 3300 | 1.1114          | 0.6332 | 0.1705 |
| 0.1011        | 60.0  | 3600 | 1.4662          | 0.6238 | 0.1794 |
| 0.0902        | 65.0  | 3900 | 1.3797          | 0.6426 | 0.1779 |
| 0.074         | 70.0  | 4200 | 1.4517          | 0.6207 | 0.1813 |
| 0.0648        | 75.0  | 4500 | 1.2976          | 0.6207 | 0.1694 |
| 0.0591        | 80.0  | 4800 | 1.3030          | 0.5987 | 0.1690 |
| 0.0622        | 85.0  | 5100 | 1.2847          | 0.5925 | 0.1636 |
| 0.0639        | 90.0  | 5400 | 1.3230          | 0.5925 | 0.1659 |
| 0.0816        | 95.0  | 5700 | 1.2766          | 0.5925 | 0.1582 |
| 0.0444        | 100.0 | 6000 | 1.2858          | 0.5831 | 0.1539 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1