metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_final
results: []
whisper_final
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.1551
- Wer: 20.6174
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: 5e-07
- train_batch_size: 8
- 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: 10
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.2932 | 0.09 | 10 | 4.6306 | 16.0442 |
| 4.2744 | 0.18 | 20 | 4.1942 | 16.2348 |
| 3.7418 | 0.27 | 30 | 3.7625 | 15.5107 |
| 3.2037 | 0.36 | 40 | 3.5635 | 14.6723 |
| 3.4714 | 0.45 | 50 | 3.4383 | 14.3674 |
| 2.8962 | 0.55 | 60 | 3.3494 | 14.1768 |
| 2.7958 | 0.64 | 70 | 3.2752 | 18.2927 |
| 2.8691 | 0.73 | 80 | 3.2208 | 19.5884 |
| 2.8693 | 0.82 | 90 | 3.1857 | 20.6174 |
| 2.9474 | 0.91 | 100 | 3.1644 | 20.6555 |
| 3.1712 | 1.0 | 110 | 3.1551 | 20.6174 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1