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: 0.2932
- Cer: 7.7185
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 |
---|---|---|---|---|
0.2477 | 0.1290 | 100 | 0.2899 | 7.8184 |
0.1437 | 0.2581 | 200 | 0.2799 | 7.4424 |
0.1141 | 0.3871 | 300 | 0.2833 | 7.3954 |
0.1071 | 0.5161 | 400 | 0.2836 | 7.7244 |
0.081 | 0.6452 | 500 | 0.2787 | 7.6010 |
0.0918 | 0.7742 | 600 | 0.2810 | 7.6774 |
0.0844 | 0.9032 | 700 | 0.2767 | 7.4601 |
0.0317 | 1.0323 | 800 | 0.2934 | 7.9065 |
0.0269 | 1.1613 | 900 | 0.2780 | 7.5247 |
0.0283 | 1.2903 | 1000 | 0.2831 | 7.6304 |
0.0301 | 1.4194 | 1100 | 0.2997 | 7.7890 |
0.0207 | 1.5484 | 1200 | 0.3091 | 7.9241 |
0.0227 | 1.6774 | 1300 | 0.2911 | 7.6480 |
0.0251 | 1.8065 | 1400 | 0.2917 | 7.7361 |
0.0231 | 1.9355 | 1500 | 0.2932 | 7.7185 |
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