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tun_wav2vec8
Myriam123/tun_wav2vec8
tun_wav2vec8 is a machine learning model from Myriam123. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- wav2vec2
- Access
- Public
- Created
- Aug 12, 2024
- Updated
- Aug 12, 2024
- SHA
- 40765f1b
Model card
From the Hugging Face model README
<!-- 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. -->
<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/> <img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>
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
- Type
- wav2vec2
- Created
- Aug 12, 2024
- Updated
- Aug 12, 2024