whisper-small-Ypause
This model is a fine-tuned version of openai/whisper-small on the aihub adult speed changed dataset. It achieves the following results on the evaluation set:
- Loss: 0.2617
- Cer: 6.5496
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Cer |
---|---|---|---|---|
0.2443 | 0.1289 | 100 | 0.2948 | 7.8830 |
0.137 | 0.2579 | 200 | 0.2761 | 7.3719 |
0.1094 | 0.3868 | 300 | 0.2806 | 7.3719 |
0.1216 | 0.5158 | 400 | 0.2647 | 7.2192 |
0.0963 | 0.6447 | 500 | 0.2679 | 7.2310 |
0.0918 | 0.7737 | 600 | 0.2690 | 7.0312 |
0.0926 | 0.9026 | 700 | 0.2676 | 7.0371 |
0.0381 | 1.0316 | 800 | 0.2591 | 6.8139 |
0.0292 | 1.1605 | 900 | 0.2618 | 6.7552 |
0.0378 | 1.2895 | 1000 | 0.2625 | 6.6964 |
0.0327 | 1.4184 | 1100 | 0.2675 | 6.6671 |
0.0371 | 1.5474 | 1200 | 0.2620 | 6.6494 |
0.0317 | 1.6763 | 1300 | 0.2607 | 6.4967 |
0.0312 | 1.8053 | 1400 | 0.2599 | 6.4850 |
0.0321 | 1.9342 | 1500 | 0.2617 | 6.5496 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
openai/whisper-small