whisper-small-_Yfreq_speed
This model is a fine-tuned version of openai/whisper-small on the aihub old adult freq speed pause changed dataset. It achieves the following results on the evaluation set:
- Loss: 0.2700
- Cer: 6.9549
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 |
---|---|---|---|---|
0.2697 | 0.1289 | 100 | 0.2973 | 8.0475 |
0.1576 | 0.2579 | 200 | 0.2714 | 7.3837 |
0.1195 | 0.3868 | 300 | 0.2826 | 7.9065 |
0.1305 | 0.5158 | 400 | 0.2721 | 7.5423 |
0.1059 | 0.6447 | 500 | 0.2775 | 7.7126 |
0.1015 | 0.7737 | 600 | 0.2747 | 7.3954 |
0.1108 | 0.9026 | 700 | 0.2697 | 7.2780 |
0.042 | 1.0309 | 800 | 0.2677 | 7.2192 |
0.0312 | 1.1599 | 900 | 0.2682 | 6.9960 |
0.0415 | 1.2888 | 1000 | 0.2678 | 7.0195 |
0.0356 | 1.4178 | 1100 | 0.2742 | 6.9725 |
0.0413 | 1.5467 | 1200 | 0.2726 | 6.8727 |
0.033 | 1.6757 | 1300 | 0.2700 | 7.0078 |
0.0345 | 1.8046 | 1400 | 0.2684 | 6.8844 |
0.0361 | 1.9336 | 1500 | 0.2700 | 6.9549 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
openai/whisper-small