whisper-large-v3-genbed-m
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6146
- Wer: 33.0189
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: 1.75e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7275 | 0.6596 | 250 | 0.7019 | 56.8503 |
| 0.469 | 1.3193 | 500 | 0.6319 | 47.4164 |
| 0.4453 | 1.9789 | 750 | 0.5507 | 42.0133 |
| 0.2294 | 2.6385 | 1000 | 0.5573 | 38.9473 |
| 0.1087 | 3.2982 | 1250 | 0.5727 | 38.6364 |
| 0.1139 | 3.9578 | 1500 | 0.5532 | 36.3422 |
| 0.0421 | 4.6174 | 1750 | 0.5786 | 35.5274 |
| 0.0173 | 5.2770 | 2000 | 0.5795 | 34.0159 |
| 0.0108 | 5.9367 | 2250 | 0.5977 | 33.5549 |
| 0.0023 | 6.5963 | 2500 | 0.6146 | 33.0189 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v3