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--- |
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language: |
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- en |
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license: apache-2.0 |
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base_model: openai/whisper-medium.en |
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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: ./800 |
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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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# ./800 |
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This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 800 SF 1000 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6191 |
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- Wer Ortho: 30.5394 |
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- Wer: 20.0215 |
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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: 3e-06 |
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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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- distributed_type: multi-GPU |
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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: 200 |
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- training_steps: 800 |
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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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| 1.2835 | 2.0 | 100 | 0.7681 | 30.5758 | 19.3039 | |
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| 0.5883 | 4.0 | 200 | 0.6235 | 27.6968 | 17.5099 | |
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| 0.3246 | 6.0 | 300 | 0.5332 | 29.4461 | 19.6268 | |
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| 0.1851 | 8.0 | 400 | 0.5366 | 34.6574 | 23.3226 | |
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| 0.1133 | 10.0 | 500 | 0.5747 | 29.9198 | 19.0886 | |
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| 0.0837 | 12.0 | 600 | 0.5947 | 30.1020 | 19.9498 | |
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| 0.0697 | 14.0 | 700 | 0.6128 | 30.3571 | 20.4521 | |
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| 0.0622 | 16.0 | 800 | 0.6191 | 30.5394 | 20.0215 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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