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tun_wav2vec5
Myriam123/tun_wav2vec5
tun_wav2vec5 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 8, 2024
- Updated
- Aug 8, 2024
- SHA
- c66b2a4e
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"/> <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"/> <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_wav2vec5
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2565
- Wer: 0.6445
- Cer: 0.1660
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: 50
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.7385 | 5.5556 | 200 | 1.1520 | 0.9062 | 0.3122 |
| 0.9367 | 11.1111 | 400 | 1.0713 | 0.8594 | 0.2677 |
| 0.5837 | 16.6667 | 600 | 1.0317 | 0.7656 | 0.2218 |
| 0.4166 | 22.2222 | 800 | 1.0374 | 0.8008 | 0.2218 |
| 0.3707 | 27.7778 | 1000 | 1.0956 | 0.7734 | 0.2157 |
| 0.2989 | 33.3333 | 1200 | 1.1494 | 0.7734 | 0.2096 |
| 0.2404 | 38.8889 | 1400 | 1.3076 | 0.7383 | 0.1960 |
| 0.2142 | 44.4444 | 1600 | 1.1622 | 0.7031 | 0.1852 |
| 0.1709 | 50.0 | 1800 | 1.1106 | 0.7227 | 0.1903 |
| 0.1599 | 55.5556 | 2000 | 1.3641 | 0.7109 | 0.1894 |
| 0.1464 | 61.1111 | 2200 | 1.3258 | 0.6992 | 0.1739 |
| 0.1283 | 66.6667 | 2400 | 1.1508 | 0.6680 | 0.1753 |
| 0.1485 | 72.2222 | 2600 | 1.3598 | 0.6484 | 0.1744 |
| 0.11 | 77.7778 | 2800 | 1.4104 | 0.6758 | 0.1810 |
| 0.0967 | 83.3333 | 3000 | 1.3813 | 0.6797 | 0.1782 |
| 0.0844 | 88.8889 | 3200 | 1.1982 | 0.6523 | 0.1697 |
| 0.0876 | 94.4444 | 3400 | 1.2400 | 0.6484 | 0.1711 |
| 0.0784 | 100.0 | 3600 | 1.2565 | 0.6445 | 0.1660 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- wav2vec2
- Created
- Aug 8, 2024
- Updated
- Aug 8, 2024