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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- p6_moderate |
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metrics: |
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- wer |
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model-index: |
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- name: p6_moderate |
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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: p6_moderate |
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type: p6_moderate |
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config: cs |
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split: test |
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args: cs |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.2500697155605131 |
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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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# p6_moderate |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the p6_moderate dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8973 |
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- Wer: 0.2501 |
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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: 5000 |
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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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| 0.0015 | 27.78 | 1000 | 0.7347 | 0.2520 | |
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| 0.0008 | 55.56 | 2000 | 0.7309 | 0.2523 | |
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| 0.0001 | 83.33 | 3000 | 0.8548 | 0.2531 | |
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| 0.0 | 111.11 | 4000 | 0.8869 | 0.2503 | |
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| 0.0 | 138.89 | 5000 | 0.8973 | 0.2501 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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