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--- |
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language: |
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- de |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: openai/whisper-base |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# openai/whisper-base |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Hanhpt23/GermanMed-full dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8154 |
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- Wer: 28.0469 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.694 | 1.0 | 194 | 0.6826 | 38.7329 | |
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| 0.3399 | 2.0 | 388 | 0.6960 | 39.2780 | |
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| 0.1866 | 3.0 | 582 | 0.7193 | 42.8057 | |
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| 0.1157 | 4.0 | 776 | 0.7415 | 31.9963 | |
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| 0.0853 | 5.0 | 970 | 0.7792 | 32.7265 | |
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| 0.0574 | 6.0 | 1164 | 0.7686 | 33.7036 | |
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| 0.0358 | 7.0 | 1358 | 0.7852 | 33.1791 | |
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| 0.0423 | 8.0 | 1552 | 0.8025 | 32.1917 | |
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| 0.027 | 9.0 | 1746 | 0.8138 | 31.2044 | |
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| 0.0172 | 10.0 | 1940 | 0.8155 | 29.0548 | |
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| 0.0182 | 11.0 | 2134 | 0.8280 | 30.7004 | |
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| 0.0053 | 12.0 | 2328 | 0.8268 | 30.4227 | |
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| 0.0066 | 13.0 | 2522 | 0.8221 | 30.0319 | |
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| 0.0023 | 14.0 | 2716 | 0.8166 | 29.5176 | |
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| 0.0007 | 15.0 | 2910 | 0.8215 | 28.6948 | |
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| 0.0012 | 16.0 | 3104 | 0.8262 | 28.4789 | |
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| 0.0003 | 17.0 | 3298 | 0.8158 | 28.3143 | |
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| 0.0004 | 18.0 | 3492 | 0.8154 | 27.9338 | |
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| 0.0003 | 19.0 | 3686 | 0.8154 | 27.9646 | |
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| 0.0003 | 20.0 | 3880 | 0.8154 | 28.0469 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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