metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: whisper-fine_tuning
results: []
whisper-fine_tuning
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: 4.4096
- Wer: 89.7704
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: 1e-06
- 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
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.127 | 0.04 | 10 | 6.5305 | 89.7704 |
| 4.9407 | 0.08 | 20 | 5.6702 | 88.1002 |
| 3.9127 | 0.12 | 30 | 5.2648 | 85.1775 |
| 3.4678 | 0.16 | 40 | 5.0057 | 84.7599 |
| 3.7416 | 0.2 | 50 | 4.8397 | 85.3862 |
| 3.1575 | 0.24 | 60 | 4.6961 | 86.4301 |
| 3.3175 | 0.28 | 70 | 4.5819 | 87.2651 |
| 2.9554 | 0.32 | 80 | 4.4950 | 88.1002 |
| 3.0291 | 0.36 | 90 | 4.4375 | 89.7704 |
| 3.0219 | 0.4 | 100 | 4.4096 | 89.7704 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1