Whisper Tiny 1000 Audios - vfranchis
This model is a fine-tuned version of openai/whisper-tiny on the 1000 audios 1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5691
- Wer: 30.7692
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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4694 | 0.4 | 25 | 1.0082 | 38.4615 |
| 0.2677 | 0.8 | 50 | 0.7480 | 46.1538 |
| 0.1034 | 1.2 | 75 | 0.6340 | 46.1538 |
| 0.0672 | 1.6 | 100 | 0.6319 | 46.1538 |
| 0.0547 | 2.0 | 125 | 0.5773 | 30.7692 |
| 0.0299 | 2.4 | 150 | 0.5612 | 30.7692 |
| 0.022 | 2.8 | 175 | 0.5784 | 30.7692 |
| 0.0218 | 3.2 | 200 | 0.5702 | 30.7692 |
| 0.0127 | 3.6 | 225 | 0.5721 | 30.7692 |
| 0.013 | 4.0 | 250 | 0.5554 | 30.7692 |
| 0.0084 | 4.4 | 275 | 0.5680 | 30.7692 |
| 0.0102 | 4.8 | 300 | 0.5691 | 30.7692 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for breco/whisper-tiny-1000-audios
Base model
openai/whisper-tiny