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openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 1.0063
- Wer: 63.1053
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: 3e-07
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 700
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4728 | 14.29 | 100 | 1.4429 | 83.5942 |
| 1.0344 | 28.57 | 200 | 1.1584 | 69.9706 |
| 0.9318 | 42.86 | 300 | 1.1061 | 67.8394 |
| 0.8882 | 57.14 | 400 | 1.0769 | 66.4290 |
| 0.8609 | 71.43 | 500 | 1.0575 | 66.1965 |
| 0.8262 | 85.71 | 600 | 1.0214 | 63.6274 |
| 0.7989 | 100.0 | 700 | 1.0063 | 63.1053 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
