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whisper-small.en
This model is a fine-tuned version of crossdelenna/whisper-small.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0003
- Wer: 0.7544
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: 16
- 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: 1001
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0017 | 0.52 | 200 | 0.0037 | 0.9845 |
0.0021 | 1.03 | 400 | 0.0006 | 0.8439 |
0.0008 | 1.55 | 600 | 0.0004 | 0.7927 |
0.0014 | 2.06 | 800 | 0.0004 | 0.7672 |
0.0004 | 2.58 | 1000 | 0.0003 | 0.7544 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3