metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-a-nomimose
results: []
whisper-a-nomimose
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: 0.0723
- Wer: 15.2655
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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.3968 | 0.9217 | 100 | 0.7677 | 512.9794 |
| 0.3388 | 1.8387 | 200 | 0.3331 | 93.3628 |
| 0.2711 | 2.7558 | 300 | 0.2512 | 87.0944 |
| 0.2383 | 3.6728 | 400 | 0.2198 | 87.9056 |
| 0.2096 | 4.5899 | 500 | 0.1971 | 80.3835 |
| 0.2131 | 5.5069 | 600 | 0.1680 | 75.5900 |
| 0.1498 | 6.4240 | 700 | 0.1433 | 56.1209 |
| 0.1152 | 7.3410 | 800 | 0.1094 | 41.0767 |
| 0.0833 | 8.2581 | 900 | 0.1193 | 65.9292 |
| 0.0653 | 9.1751 | 1000 | 0.0728 | 25.1475 |
| 0.0444 | 10.0922 | 1100 | 0.0781 | 24.4100 |
| 0.0383 | 11.0092 | 1200 | 0.0537 | 17.6991 |
| 0.0269 | 11.9309 | 1300 | 0.0658 | 18.0678 |
| 0.0182 | 12.8479 | 1400 | 0.0641 | 19.3215 |
| 0.0128 | 13.7650 | 1500 | 0.0679 | 15.8555 |
| 0.0068 | 14.6820 | 1600 | 0.0723 | 15.2655 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0