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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-medium |
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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-medium |
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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-medium |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Hanhpt23/GermanMed-full dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8743 |
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- Wer: 26.2573 |
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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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| 0.7043 | 1.0 | 194 | 0.7433 | 43.3508 | |
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| 0.4383 | 2.0 | 388 | 0.7578 | 37.6118 | |
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| 0.28 | 3.0 | 582 | 0.8223 | 39.6380 | |
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| 0.188 | 4.0 | 776 | 0.8428 | 35.1538 | |
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| 0.1479 | 5.0 | 970 | 0.8755 | 32.6751 | |
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| 0.1263 | 6.0 | 1164 | 0.8562 | 31.2249 | |
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| 0.0808 | 7.0 | 1358 | 0.8797 | 31.5129 | |
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| 0.063 | 8.0 | 1552 | 0.9294 | 33.3333 | |
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| 0.0469 | 9.0 | 1746 | 0.9285 | 35.4315 | |
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| 0.0464 | 10.0 | 1940 | 0.9110 | 29.5176 | |
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| 0.0302 | 11.0 | 2134 | 0.9158 | 33.4568 | |
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| 0.0355 | 12.0 | 2328 | 0.9420 | 31.9243 | |
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| 0.0167 | 13.0 | 2522 | 0.9098 | 30.6284 | |
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| 0.0119 | 14.0 | 2716 | 0.8894 | 29.7645 | |
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| 0.0092 | 15.0 | 2910 | 0.8861 | 26.9567 | |
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| 0.0034 | 16.0 | 3104 | 0.8764 | 26.9670 | |
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| 0.0007 | 17.0 | 3298 | 0.8692 | 26.2573 | |
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| 0.0007 | 18.0 | 3492 | 0.8724 | 26.6584 | |
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| 0.0002 | 19.0 | 3686 | 0.8739 | 26.2265 | |
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| 0.0002 | 20.0 | 3880 | 0.8743 | 26.2573 | |
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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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