tun_wav2vec_final / README.md
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---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: tun_wav2vec_final
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_wav2vec_final
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3109
- Wer: 0.5737
- Cer: 0.1609
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.2068 | 5.0 | 300 | 0.9499 | 0.6270 | 0.1709 |
| 0.1824 | 10.0 | 600 | 1.1143 | 0.6395 | 0.1740 |
| 0.1519 | 15.0 | 900 | 1.4216 | 0.6520 | 0.1852 |
| 0.1387 | 20.0 | 1200 | 1.1372 | 0.6176 | 0.1632 |
| 0.1221 | 25.0 | 1500 | 1.3203 | 0.6364 | 0.1694 |
| 0.1182 | 30.0 | 1800 | 1.3959 | 0.6270 | 0.1782 |
| 0.099 | 35.0 | 2100 | 1.6996 | 0.6176 | 0.1798 |
| 0.1098 | 40.0 | 2400 | 1.3228 | 0.6113 | 0.1713 |
| 0.0834 | 45.0 | 2700 | 1.2459 | 0.6082 | 0.1582 |
| 0.0801 | 50.0 | 3000 | 1.1573 | 0.5956 | 0.1516 |
| 0.107 | 55.0 | 3300 | 1.2025 | 0.6019 | 0.1640 |
| 0.0954 | 60.0 | 3600 | 1.2703 | 0.5611 | 0.1593 |
| 0.0581 | 65.0 | 3900 | 1.2382 | 0.5768 | 0.1566 |
| 0.0582 | 70.0 | 4200 | 1.1088 | 0.5799 | 0.1566 |
| 0.0434 | 75.0 | 4500 | 1.3048 | 0.5831 | 0.1597 |
| 0.0451 | 80.0 | 4800 | 1.3257 | 0.5768 | 0.1640 |
| 0.0383 | 85.0 | 5100 | 1.3002 | 0.5611 | 0.1532 |
| 0.0384 | 90.0 | 5400 | 1.4335 | 0.5768 | 0.1620 |
| 0.0518 | 95.0 | 5700 | 1.2875 | 0.5737 | 0.1570 |
| 0.0434 | 100.0 | 6000 | 1.3109 | 0.5737 | 0.1609 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1