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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-tiny |
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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-tiny |
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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-tiny |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Hanhpt23/GermanMed-full dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9014 |
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- Wer: 29.3839 |
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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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| 0.747 | 1.0 | 194 | 0.7466 | 40.1728 | |
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| 0.4004 | 2.0 | 388 | 0.7261 | 37.1285 | |
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| 0.2012 | 3.0 | 582 | 0.7231 | 34.3721 | |
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| 0.1134 | 4.0 | 776 | 0.7465 | 34.0327 | |
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| 0.0606 | 5.0 | 970 | 0.7888 | 37.7044 | |
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| 0.0525 | 6.0 | 1164 | 0.8147 | 33.9813 | |
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| 0.0323 | 7.0 | 1358 | 0.8244 | 31.6569 | |
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| 0.027 | 8.0 | 1552 | 0.8383 | 31.8215 | |
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| 0.0149 | 9.0 | 1746 | 0.8643 | 32.1094 | |
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| 0.0119 | 10.0 | 1940 | 0.8747 | 31.7495 | |
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| 0.009 | 11.0 | 2134 | 0.8765 | 30.9781 | |
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| 0.0037 | 12.0 | 2328 | 0.8875 | 29.8879 | |
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| 0.0021 | 13.0 | 2522 | 0.8832 | 30.0936 | |
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| 0.0011 | 14.0 | 2716 | 0.8943 | 29.9496 | |
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| 0.0013 | 15.0 | 2910 | 0.8906 | 29.5485 | |
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| 0.0006 | 16.0 | 3104 | 0.8944 | 29.5999 | |
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| 0.0006 | 17.0 | 3298 | 0.8968 | 29.3942 | |
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| 0.0005 | 18.0 | 3492 | 0.8997 | 29.3839 | |
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| 0.0006 | 19.0 | 3686 | 0.9010 | 29.4251 | |
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| 0.0005 | 20.0 | 3880 | 0.9014 | 29.3839 | |
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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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