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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: openai/whisper-large-v3 |
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model-index: |
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- name: whisper-large-v3-MH-fine-tuned |
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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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# whisper-large-v3-MH-fine-tuned |
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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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- eval_loss: 0.6698 |
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- eval_runtime: 7.0899 |
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- eval_samples_per_second: 0.987 |
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- eval_steps_per_second: 0.282 |
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- epoch: 16.0 |
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- step: 112 |
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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: 0.001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 10 |
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- num_epochs: 25 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- PEFT 0.11.2.dev0 |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
