openai/whisper-base
This model is a fine-tuned version of openai/whisper-base on the Hanhpt23/GermanMed-full dataset. It achieves the following results on the evaluation set:
- Loss: 0.8154
- Wer: 28.0469
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: 0.0001
- train_batch_size: 8
- 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: 100
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.694 | 1.0 | 194 | 0.6826 | 38.7329 |
0.3399 | 2.0 | 388 | 0.6960 | 39.2780 |
0.1866 | 3.0 | 582 | 0.7193 | 42.8057 |
0.1157 | 4.0 | 776 | 0.7415 | 31.9963 |
0.0853 | 5.0 | 970 | 0.7792 | 32.7265 |
0.0574 | 6.0 | 1164 | 0.7686 | 33.7036 |
0.0358 | 7.0 | 1358 | 0.7852 | 33.1791 |
0.0423 | 8.0 | 1552 | 0.8025 | 32.1917 |
0.027 | 9.0 | 1746 | 0.8138 | 31.2044 |
0.0172 | 10.0 | 1940 | 0.8155 | 29.0548 |
0.0182 | 11.0 | 2134 | 0.8280 | 30.7004 |
0.0053 | 12.0 | 2328 | 0.8268 | 30.4227 |
0.0066 | 13.0 | 2522 | 0.8221 | 30.0319 |
0.0023 | 14.0 | 2716 | 0.8166 | 29.5176 |
0.0007 | 15.0 | 2910 | 0.8215 | 28.6948 |
0.0012 | 16.0 | 3104 | 0.8262 | 28.4789 |
0.0003 | 17.0 | 3298 | 0.8158 | 28.3143 |
0.0004 | 18.0 | 3492 | 0.8154 | 27.9338 |
0.0003 | 19.0 | 3686 | 0.8154 | 27.9646 |
0.0003 | 20.0 | 3880 | 0.8154 | 28.0469 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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