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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: 0.9461 |
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- Wer: 30.9061 |
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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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| 0.8146 | 1.0 | 194 | 0.8137 | 65.1856 | |
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| 0.4421 | 2.0 | 388 | 0.8220 | 37.1285 | |
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| 0.2251 | 3.0 | 582 | 0.7980 | 39.5557 | |
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| 0.1636 | 4.0 | 776 | 0.8563 | 50.7457 | |
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| 0.0827 | 5.0 | 970 | 0.8480 | 40.8516 | |
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| 0.0772 | 6.0 | 1164 | 0.8860 | 43.8136 | |
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| 0.0437 | 7.0 | 1358 | 0.9120 | 37.8793 | |
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| 0.0328 | 8.0 | 1552 | 0.9252 | 34.8144 | |
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| 0.0222 | 9.0 | 1746 | 0.9330 | 35.4520 | |
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| 0.0216 | 10.0 | 1940 | 0.9464 | 33.9504 | |
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| 0.0145 | 11.0 | 2134 | 0.9413 | 32.3151 | |
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| 0.0072 | 12.0 | 2328 | 0.9746 | 33.8990 | |
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| 0.0045 | 13.0 | 2522 | 0.9515 | 32.3871 | |
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| 0.0024 | 14.0 | 2716 | 0.9588 | 34.3618 | |
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| 0.0031 | 15.0 | 2910 | 0.9483 | 34.0533 | |
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| 0.0006 | 16.0 | 3104 | 0.9485 | 30.8135 | |
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| 0.0005 | 17.0 | 3298 | 0.9433 | 30.8444 | |
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| 0.0004 | 18.0 | 3492 | 0.9449 | 31.0398 | |
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| 0.0004 | 19.0 | 3686 | 0.9457 | 30.9575 | |
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| 0.0004 | 20.0 | 3880 | 0.9461 | 30.9061 | |
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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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