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whisper-medium-ln-ojpl-2
This model is a fine-tuned version of openai/whisper-medium on the BrainTheos/ojpl dataset. It achieves the following results on the evaluation set:
- Loss: 1.1202
- Wer Ortho: 35.8309
- Wer: 0.2901
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0172 | 23.19 | 1000 | 0.9966 | 41.9139 | 0.3407 |
| 0.0053 | 46.38 | 2000 | 1.0716 | 37.0920 | 0.2996 |
| 0.0034 | 69.57 | 3000 | 1.1329 | 36.0163 | 0.2850 |
| 0.0021 | 92.75 | 4000 | 1.1202 | 35.8309 | 0.2901 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
