AIHub_non-face-to-face-care_data_model_synthesis
This model is a fine-tuned version of openai/whisper-base on the AIHub_non-face-to-face-care_data dataset. It achieves the following results on the evaluation set:
- Loss: 0.4661
- Cer: 86.6106
- Normalized Cer: 0.1083
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Normalized Cer |
|---|---|---|---|---|---|
| 0.6939 | 2.5 | 1000 | 0.7123 | 100.3264 | 0.1254 |
| 0.4626 | 5.0 | 2000 | 0.4787 | 93.8130 | 0.1173 |
| 0.3828 | 7.5 | 3000 | 0.4661 | 86.6106 | 0.1083 |
| 0.3207 | 10.0 | 4000 | 0.4811 | 99.8114 | 0.1248 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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