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--- |
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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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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper da-nst |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_17_0 |
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type: common_voice_17_0 |
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config: da |
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split: test |
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args: da |
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metrics: |
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- name: Wer |
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type: wer |
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value: 28.635316438541807 |
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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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# Whisper da-nst |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8780 |
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- Wer: 28.6353 |
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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: 1e-05 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 500 |
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- training_steps: 11000 |
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- mixed_precision_training: Native AMP |
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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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| 0.0096 | 4.01 | 1000 | 0.7403 | 31.2960 | |
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| 0.0046 | 9.0 | 2000 | 0.7646 | 29.8505 | |
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| 0.0016 | 13.02 | 3000 | 0.7695 | 30.8398 | |
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| 0.0009 | 18.01 | 4000 | 0.7821 | 31.2102 | |
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| 0.0006 | 22.02 | 5000 | 0.8035 | 31.6303 | |
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| 0.0011 | 27.01 | 6000 | 0.8169 | 29.6336 | |
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| 0.0001 | 32.0 | 7000 | 0.8244 | 29.6246 | |
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| 0.0 | 36.01 | 8000 | 0.8461 | 28.8205 | |
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| 0.0 | 41.01 | 9000 | 0.8633 | 28.7754 | |
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| 0.0 | 45.02 | 10000 | 0.8738 | 28.6986 | |
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| 0.0 | 50.01 | 11000 | 0.8780 | 28.6353 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.1 |
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