metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_M01
results: []
torgo_tiny_finetune_M01
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3526
- Wer: 96.6044
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: 16
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6272 | 0.85 | 500 | 0.2872 | 24.1087 |
| 0.1055 | 1.7 | 1000 | 0.3364 | 77.5042 |
| 0.0998 | 2.55 | 1500 | 0.3646 | 65.8744 |
| 0.0635 | 3.4 | 2000 | 0.3276 | 34.9745 |
| 0.0521 | 4.24 | 2500 | 0.3619 | 31.8336 |
| 0.0368 | 5.09 | 3000 | 0.3158 | 43.0390 |
| 0.0269 | 5.94 | 3500 | 0.3424 | 53.7351 |
| 0.0215 | 6.79 | 4000 | 0.2886 | 48.8964 |
| 0.0182 | 7.64 | 4500 | 0.3331 | 31.0696 |
| 0.0135 | 8.49 | 5000 | 0.3308 | 45.0764 |
| 0.0092 | 9.34 | 5500 | 0.2825 | 28.9474 |
| 0.0088 | 10.19 | 6000 | 0.3169 | 32.3430 |
| 0.0056 | 11.04 | 6500 | 0.3223 | 55.7725 |
| 0.0034 | 11.88 | 7000 | 0.3396 | 30.2207 |
| 0.0041 | 12.73 | 7500 | 0.3403 | 31.8336 |
| 0.0031 | 13.58 | 8000 | 0.3544 | 138.4550 |
| 0.0023 | 14.43 | 8500 | 0.3357 | 54.8387 |
| 0.0004 | 15.28 | 9000 | 0.3618 | 53.6503 |
| 0.0003 | 16.13 | 9500 | 0.3598 | 74.3633 |
| 0.0002 | 16.98 | 10000 | 0.3536 | 98.8964 |
| 0.0003 | 17.83 | 10500 | 0.3529 | 95.8404 |
| 0.0001 | 18.68 | 11000 | 0.3505 | 98.0475 |
| 0.0001 | 19.52 | 11500 | 0.3526 | 96.6044 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3