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whisper-tiny-ASR
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8363
- Wer: 60.1936
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1494 | 6.8 | 1000 | 0.4732 | 50.4342 |
0.0113 | 13.61 | 2000 | 0.6944 | 62.9461 |
0.0024 | 20.41 | 3000 | 0.8042 | 59.8032 |
0.0014 | 27.21 | 4000 | 0.8363 | 60.1936 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1