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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_M01_frozen_encoder |
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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_M01_frozen_encoder |
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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: 0.2864 |
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- Wer: 45.6706 |
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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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| 0.768 | 0.85 | 500 | 0.2601 | 25.8913 | |
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| 0.0914 | 1.7 | 1000 | 0.2569 | 99.8302 | |
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| 0.0699 | 2.55 | 1500 | 0.2626 | 39.3039 | |
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| 0.042 | 3.4 | 2000 | 0.2691 | 26.0611 | |
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| 0.0336 | 4.24 | 2500 | 0.2619 | 25.4669 | |
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| 0.0229 | 5.09 | 3000 | 0.2613 | 29.2020 | |
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| 0.0166 | 5.94 | 3500 | 0.2525 | 30.0509 | |
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| 0.0112 | 6.79 | 4000 | 0.2843 | 30.7301 | |
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| 0.0113 | 7.64 | 4500 | 0.2862 | 25.8913 | |
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| 0.0085 | 8.49 | 5000 | 0.2726 | 29.5416 | |
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| 0.0059 | 9.34 | 5500 | 0.2782 | 35.6537 | |
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| 0.0052 | 10.19 | 6000 | 0.2971 | 39.6435 | |
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| 0.0041 | 11.04 | 6500 | 0.2886 | 26.9949 | |
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| 0.0043 | 11.88 | 7000 | 0.2952 | 29.2869 | |
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| 0.0031 | 12.73 | 7500 | 0.2858 | 34.3803 | |
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| 0.0022 | 13.58 | 8000 | 0.2844 | 35.9083 | |
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| 0.0019 | 14.43 | 8500 | 0.2749 | 33.7861 | |
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| 0.0013 | 15.28 | 9000 | 0.2882 | 41.3413 | |
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| 0.0014 | 16.13 | 9500 | 0.2817 | 44.3973 | |
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| 0.0008 | 16.98 | 10000 | 0.2872 | 39.7284 | |
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| 0.0006 | 17.83 | 10500 | 0.2846 | 41.8506 | |
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| 0.0003 | 18.68 | 11000 | 0.2900 | 45.2462 | |
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| 0.0003 | 19.52 | 11500 | 0.2864 | 45.6706 | |
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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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