whisper-finetuned
This model is a fine-tuned version of openai/whisper-base.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1346
- Wer: 7.2378
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: 500
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.6697 | 0.27 | 200 | 0.6175 | 9.3248 |
0.1957 | 0.54 | 400 | 0.1761 | 8.2947 |
0.1476 | 0.81 | 600 | 0.1458 | 7.5990 |
0.0939 | 1.09 | 800 | 0.1372 | 7.4920 |
0.086 | 1.36 | 1000 | 0.1346 | 7.2378 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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