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--- |
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library_name: transformers |
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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: whisper-large-v3-cit-do015-wd0-lr1e-06-FULL4 |
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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-cit-do015-wd0-lr1e-06-FULL4 |
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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: 0.5059 |
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- Wer Ortho: 28.4797 |
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- Wer: 21.0751 |
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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-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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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: 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: 300 |
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- training_steps: 1400 |
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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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
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| 0.9206 | 0.7715 | 200 | 0.6309 | 33.9104 | 25.9900 | |
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| 0.6533 | 1.5429 | 400 | 0.5581 | 30.2736 | 22.5910 | |
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| 0.5875 | 2.3144 | 600 | 0.5322 | 29.5128 | 22.8648 | |
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| 0.5351 | 3.0858 | 800 | 0.5176 | 29.3103 | 21.8431 | |
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| 0.5126 | 3.8573 | 1000 | 0.5112 | 28.7100 | 21.3222 | |
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| 0.4956 | 4.6287 | 1200 | 0.5063 | 28.6053 | 21.0751 | |
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| 0.4785 | 5.4002 | 1400 | 0.5059 | 28.4797 | 21.0751 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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