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whisper-small-ko-EYfreqspeed
This model is a fine-tuned version of openai/whisper-small on the aihub Y dialogue dataset. It achieves the following results on the evaluation set:
- Loss: 0.2179
- Cer: 21.0586
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.4086 | 0.3 | 100 | 0.2539 | 6.5745 |
| 0.3177 | 0.59 | 200 | 0.2342 | 6.3728 |
| 0.2886 | 0.89 | 300 | 0.2193 | 5.7557 |
| 0.1251 | 1.19 | 400 | 0.2201 | 5.9515 |
| 0.1171 | 1.48 | 500 | 0.2302 | 6.7762 |
| 0.1033 | 1.78 | 600 | 0.2181 | 5.6429 |
| 0.0363 | 2.07 | 700 | 0.2154 | 5.7616 |
| 0.039 | 2.37 | 800 | 0.2180 | 7.3874 |
| 0.0399 | 2.67 | 900 | 0.2113 | 17.4094 |
| 0.0367 | 2.96 | 1000 | 0.2080 | 14.2645 |
| 0.0146 | 3.26 | 1100 | 0.2151 | 16.5074 |
| 0.0128 | 3.56 | 1200 | 0.2155 | 20.8331 |
| 0.013 | 3.85 | 1300 | 0.2159 | 12.1225 |
| 0.0049 | 4.15 | 1400 | 0.2159 | 18.2757 |
| 0.0043 | 4.44 | 1500 | 0.2166 | 22.0970 |
| 0.0037 | 4.74 | 1600 | 0.2179 | 21.0586 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
