Whisper Base finetune - rab796
This model is a fine-tuned version of openai/whisper-base on the whisper_finetune_data2_240120 dataset. It achieves the following results on the evaluation set:
- Loss: 1.3989
- Cer: 27.6596
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: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.0001 | 500.0 | 1000 | 1.3218 | 26.9504 |
| 0.0 | 1000.0 | 2000 | 1.3690 | 27.3050 |
| 0.0 | 1500.0 | 3000 | 1.3913 | 27.6596 |
| 0.0 | 2000.0 | 4000 | 1.3989 | 27.6596 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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