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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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metrics: |
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- wer |
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model-index: |
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- name: finetune_v3 |
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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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# finetune_v3 |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1775 |
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- Wer: 13.8249 |
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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: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 5 |
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- training_steps: 40 |
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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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| No log | 6.6667 | 10 | 0.2449 | 19.8157 | |
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| No log | 13.3333 | 20 | 0.1967 | 14.5161 | |
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| No log | 20.0 | 30 | 0.1821 | 14.2857 | |
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| No log | 26.6667 | 40 | 0.1775 | 13.8249 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.2.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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