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tun_wav2vec7
Myriam123/tun_wav2vec7
tun_wav2vec7 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 11, 2024
- Updated
- Aug 11, 2024
- SHA
- 9ebb2c66
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_wav2vec7
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2586
- Wer: 0.5945
- Cer: 0.1592
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: 70
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 2.0634 | 5.4545 | 300 | 1.3331 | 0.9794 | 0.3126 |
| 0.7466 | 10.9091 | 600 | 1.1736 | 0.8522 | 0.2637 |
| 0.496 | 16.3636 | 900 | 1.0844 | 0.8076 | 0.2344 |
| 0.3864 | 21.8182 | 1200 | 1.5553 | 0.7766 | 0.2436 |
| 0.2908 | 27.2727 | 1500 | 1.1381 | 0.7045 | 0.2089 |
| 0.2241 | 32.7273 | 1800 | 1.4912 | 0.7182 | 0.2236 |
| 0.175 | 38.1818 | 2100 | 1.1890 | 0.6426 | 0.1910 |
| 0.1483 | 43.6364 | 2400 | 1.1582 | 0.6323 | 0.1667 |
| 0.1237 | 49.0909 | 2700 | 1.2264 | 0.6357 | 0.1722 |
| 0.1676 | 54.5455 | 3000 | 1.1899 | 0.6632 | 0.1726 |
| 0.1437 | 60.0 | 3300 | 1.2421 | 0.6323 | 0.1793 |
| 0.1261 | 65.4545 | 3600 | 1.2693 | 0.6117 | 0.1663 |
| 0.0787 | 70.9091 | 3900 | 1.2301 | 0.6014 | 0.1601 |
| 0.0952 | 76.3636 | 4200 | 1.2063 | 0.6186 | 0.1659 |
| 0.1385 | 81.8182 | 4500 | 1.2732 | 0.6082 | 0.1642 |
| 0.0659 | 87.2727 | 4800 | 1.3254 | 0.6048 | 0.1692 |
| 0.058 | 92.7273 | 5100 | 1.2216 | 0.5979 | 0.1575 |
| 0.1454 | 98.1818 | 5400 | 1.2586 | 0.5945 | 0.1592 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- wav2vec2
- Created
- Aug 11, 2024
- Updated
- Aug 11, 2024