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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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