<!-- 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. -->
wav2vec2-model2-torgo
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.9975
- Wer: 1.0
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: 0.1
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 12.5453 | 0.76 | 500 | 14.6490 | 1.0 |
| 4.8036 | 1.53 | 1000 | 8.4523 | 1.0 |
| 5.0421 | 2.29 | 1500 | 5.4114 | 1.0 |
| 5.2055 | 3.05 | 2000 | 11.0507 | 1.0 |
| 4.6389 | 3.82 | 2500 | 4.6792 | 1.0 |
| 4.5523 | 4.58 | 3000 | 4.7855 | 1.0 |
| 4.7843 | 5.34 | 3500 | 11.2783 | 1.0 |
| 4.6066 | 6.11 | 4000 | 8.7807 | 1.0 |
| 4.7382 | 6.87 | 4500 | 2942.0220 | 1.0 |
| 130.5733 | 7.63 | 5000 | 5.8412 | 1.0 |
| 4.4972 | 8.4 | 5500 | 17.7038 | 1.0 |
| 4.5196 | 9.16 | 6000 | 11.4548 | 1.0 |
| 4.3198 | 9.92 | 6500 | 6.0885 | 1.0 |
| 4.4273 | 10.69 | 7000 | 6.7374 | 1.0 |
| 4.2783 | 11.45 | 7500 | 4.7276 | 1.0 |
| 4.2985 | 12.21 | 8000 | 6.1412 | 1.0 |
| 4.3262 | 12.98 | 8500 | 5.2621 | 1.0 |
| 4.1705 | 13.74 | 9000 | 5.2214 | 1.0 |
| 4.3176 | 14.5 | 9500 | 5.5359 | 1.0 |
| 3.9808 | 15.27 | 10000 | 4.1537 | 1.0 |
| 4.0228 | 16.03 | 10500 | 4.2962 | 1.0 |
| 4.0595 | 16.79 | 11000 | 7.6361 | 1.0 |
| 4.0088 | 17.56 | 11500 | 6.8715 | 1.0 |
| 3.8727 | 18.32 | 12000 | 8.8657 | 1.0 |
| 4.0073 | 19.08 | 12500 | 5.8170 | 1.0 |
| 3.8511 | 19.85 | 13000 | 13.9836 | 1.0 |
| 4.0899 | 20.61 | 13500 | 5.3287 | 1.0 |
| 3.8782 | 21.37 | 14000 | 8.0635 | 1.0 |
| 3.9235 | 22.14 | 14500 | 5.5129 | 1.0 |
| 3.7276 | 22.9 | 15000 | 5.0819 | 1.0 |
| 3.7908 | 23.66 | 15500 | 6.1458 | 1.0 |
| 3.9176 | 24.43 | 16000 | 4.6094 | 1.0 |
| 3.8477 | 25.19 | 16500 | 5.1406 | 1.0 |
| 3.6917 | 25.95 | 17000 | 4.5684 | 1.0 |
| 3.8568 | 26.72 | 17500 | 4.0306 | 1.0 |
| 3.7231 | 27.48 | 18000 | 5.6331 | 1.0 |
| 3.8145 | 28.24 | 18500 | 8.2997 | 1.0 |
| 3.7809 | 29.01 | 19000 | 5.7468 | 1.0 |
| 3.5995 | 29.77 | 19500 | 4.9975 | 1.0 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 1.18.3
- Tokenizers 0.11.6
