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whisper-l3
This model is a fine-tuned version of openai/whisper-large-v3 on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.8569
- Wer Ortho: 66.8317
- Wer: 69.5276
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 2
- training_steps: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.418 | 0.064 | 1 | 2.0816 | 66.7327 | 70.0 |
| 1.2547 | 0.128 | 2 | 2.0508 | 66.8317 | 70.1575 |
| 1.3085 | 0.192 | 3 | 1.9875 | 66.5347 | 70.0787 |
| 1.2471 | 0.256 | 4 | 1.9218 | 66.7327 | 70.2362 |
| 1.1331 | 0.32 | 5 | 1.8569 | 66.8317 | 69.5276 |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v3