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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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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: torgo_tiny_finetune_F03 |
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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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# torgo_tiny_finetune_F03 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0640 |
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- Wer: 15.0892 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 1 |
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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: 1000 |
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- num_epochs: 20 |
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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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| 0.6368 | 0.85 | 500 | 0.1136 | 7.8189 | |
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| 0.11 | 1.69 | 1000 | 0.0872 | 9.1907 | |
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| 0.0969 | 2.54 | 1500 | 0.0843 | 9.3278 | |
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| 0.0679 | 3.39 | 2000 | 0.0980 | 7.1331 | |
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| 0.053 | 4.24 | 2500 | 0.0756 | 7.1331 | |
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| 0.0361 | 5.08 | 3000 | 0.0637 | 9.1907 | |
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| 0.0278 | 5.93 | 3500 | 0.0491 | 8.3676 | |
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| 0.0233 | 6.78 | 4000 | 0.0446 | 27.8464 | |
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| 0.0148 | 7.63 | 4500 | 0.0403 | 12.8944 | |
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| 0.0149 | 8.47 | 5000 | 0.0748 | 28.6694 | |
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| 0.0105 | 9.32 | 5500 | 0.0631 | 17.6955 | |
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| 0.0087 | 10.17 | 6000 | 0.0619 | 12.0713 | |
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| 0.0075 | 11.02 | 6500 | 0.0525 | 18.6557 | |
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| 0.004 | 11.86 | 7000 | 0.0588 | 19.7531 | |
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| 0.0039 | 12.71 | 7500 | 0.0618 | 24.5542 | |
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| 0.0029 | 13.56 | 8000 | 0.0915 | 13.7174 | |
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| 0.0022 | 14.41 | 8500 | 0.0638 | 20.4390 | |
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| 0.0013 | 15.25 | 9000 | 0.0946 | 14.5405 | |
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| 0.0004 | 16.1 | 9500 | 0.0746 | 15.7750 | |
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| 0.0003 | 16.95 | 10000 | 0.0633 | 11.2483 | |
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| 0.0001 | 17.8 | 10500 | 0.0645 | 12.7572 | |
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| 0.0001 | 18.64 | 11000 | 0.0631 | 14.4033 | |
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| 0.0001 | 19.49 | 11500 | 0.0640 | 15.0892 | |
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### Framework versions |
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- Transformers 4.32.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.7 |
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- Tokenizers 0.13.3 |
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