Whisper Large V2
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3623
- Wer: 21.2197
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-05
- train_batch_size: 12
- 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: 20
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5651 | 0.75 | 15 | 0.4091 | 25.8916 |
| 0.2755 | 1.5 | 30 | 0.3437 | 23.1455 |
| 0.1284 | 2.25 | 45 | 0.3333 | 19.0086 |
| 0.0768 | 3.0 | 60 | 0.3305 | 27.7461 |
| 0.0365 | 3.75 | 75 | 0.3449 | 24.8752 |
| 0.0224 | 4.5 | 90 | 0.3623 | 21.2197 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v2