whisper_tuning_2
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: 3.8171
- Wer: 22.0048
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 |
|---|---|---|---|---|
| 4.9019 | 0.2 | 10 | 4.7994 | 22.8435 |
| 4.8102 | 0.4 | 20 | 4.3818 | 22.7236 |
| 4.1548 | 0.6 | 30 | 4.0237 | 22.4042 |
| 4.0853 | 0.8 | 40 | 3.8926 | 22.1246 |
| 3.6087 | 1.0 | 50 | 3.8171 | 22.0048 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Model tree for RecCode/whisper_tuning_2
Base model
openai/whisper-small