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openai/whisper-medium.en
This model is a fine-tuned version of openai/whisper-medium.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4522
- Wer: 10.7946
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: 32
- 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 |
---|---|---|---|---|
0.2652 | 0.12 | 500 | 0.3042 | 11.2277 |
0.2102 | 1.11 | 1000 | 0.2824 | 10.9156 |
0.1913 | 2.1 | 1500 | 0.2924 | 11.2366 |
0.0249 | 3.09 | 2000 | 0.3386 | 10.6246 |
0.031 | 4.07 | 2500 | 0.3798 | 11.1400 |
0.0224 | 5.06 | 3000 | 0.4086 | 10.9767 |
0.0033 | 6.05 | 3500 | 0.4452 | 10.3392 |
0.0028 | 7.03 | 4000 | 0.4522 | 10.7946 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2