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--- |
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language: |
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- he |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- hf-asr-leaderboard |
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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: he-cantillation |
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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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# he-cantillation |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1579 |
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- Wer: 12.5795 |
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- Avg Precision Exact: 0.8918 |
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- Avg Recall Exact: 0.8920 |
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- Avg F1 Exact: 0.8915 |
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- Avg Precision Letter Shift: 0.9121 |
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- Avg Recall Letter Shift: 0.9126 |
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- Avg F1 Letter Shift: 0.9120 |
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- Avg Precision Word Level: 0.9146 |
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- Avg Recall Word Level: 0.9150 |
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- Avg F1 Word Level: 0.9144 |
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- Avg Precision Word Shift: 0.9737 |
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- Avg Recall Word Shift: 0.9750 |
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- Avg F1 Word Shift: 0.9739 |
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- Precision Median Exact: 1.0 |
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- Recall Median Exact: 1.0 |
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- F1 Median Exact: 1.0 |
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- Precision Max Exact: 1.0 |
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- Recall Max Exact: 1.0 |
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- F1 Max Exact: 1.0 |
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- Precision Min Exact: 0.0 |
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- Recall Min Exact: 0.0 |
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- F1 Min Exact: 0.0 |
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- Precision Min Letter Shift: 0.0 |
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- Recall Min Letter Shift: 0.0 |
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- F1 Min Letter Shift: 0.0 |
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- Precision Min Word Level: 0.0 |
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- Recall Min Word Level: 0.0 |
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- F1 Min Word Level: 0.0 |
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- Precision Min Word Shift: 0.1429 |
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- Recall Min Word Shift: 0.1 |
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- F1 Min Word Shift: 0.1176 |
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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-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 32 |
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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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- training_steps: 50000 |
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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 | Avg Precision Exact | Avg Recall Exact | Avg F1 Exact | Avg Precision Letter Shift | Avg Recall Letter Shift | Avg F1 Letter Shift | Avg Precision Word Level | Avg Recall Word Level | Avg F1 Word Level | Avg Precision Word Shift | Avg Recall Word Shift | Avg F1 Word Shift | Precision Median Exact | Recall Median Exact | F1 Median Exact | Precision Max Exact | Recall Max Exact | F1 Max Exact | Precision Min Exact | Recall Min Exact | F1 Min Exact | Precision Min Letter Shift | Recall Min Letter Shift | F1 Min Letter Shift | Precision Min Word Level | Recall Min Word Level | F1 Min Word Level | Precision Min Word Shift | Recall Min Word Shift | F1 Min Word Shift | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:| |
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| 0.0443 | 0.4 | 5000 | 0.1428 | 18.7251 | 0.8438 | 0.8491 | 0.8459 | 0.8710 | 0.8764 | 0.8731 | 0.8744 | 0.8797 | 0.8765 | 0.9469 | 0.9529 | 0.9492 | 0.9167 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0165 | 0.8 | 10000 | 0.1359 | 15.5691 | 0.8644 | 0.8668 | 0.8652 | 0.8882 | 0.8907 | 0.8890 | 0.8912 | 0.8938 | 0.8920 | 0.9621 | 0.9653 | 0.9632 | 0.9310 | 0.9375 | 0.9474 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | |
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| 0.0282 | 1.2 | 15000 | 0.1395 | 14.6859 | 0.8710 | 0.8721 | 0.8712 | 0.8930 | 0.8941 | 0.8931 | 0.8960 | 0.8971 | 0.8961 | 0.9660 | 0.9672 | 0.9662 | 0.9375 | 0.9412 | 0.9524 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1111 | 0.1 | 0.1176 | |
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| 0.0076 | 1.6 | 20000 | 0.1468 | 13.9542 | 0.8822 | 0.8850 | 0.8832 | 0.9040 | 0.9069 | 0.9051 | 0.9067 | 0.9098 | 0.9078 | 0.9672 | 0.9717 | 0.9689 | 0.9375 | 1.0 | 0.9565 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | |
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| 0.0075 | 2.0 | 25000 | 0.1491 | 13.6179 | 0.8854 | 0.8860 | 0.8853 | 0.9067 | 0.9073 | 0.9066 | 0.9092 | 0.9101 | 0.9092 | 0.9685 | 0.9698 | 0.9686 | 1.0 | 1.0 | 0.9630 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | |
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| 0.0033 | 2.4 | 30000 | 0.1531 | 13.2114 | 0.8901 | 0.8900 | 0.8897 | 0.9102 | 0.9101 | 0.9097 | 0.9126 | 0.9127 | 0.9122 | 0.9712 | 0.9723 | 0.9713 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | |
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| 0.0045 | 2.8 | 35000 | 0.1535 | 13.0488 | 0.8920 | 0.8921 | 0.8916 | 0.9129 | 0.9131 | 0.9126 | 0.9153 | 0.9155 | 0.9150 | 0.9726 | 0.9734 | 0.9725 | 1.0 | 1.0 | 0.9697 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | |
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| 0.0011 | 3.2 | 40000 | 0.1543 | 12.9084 | 0.8924 | 0.8940 | 0.8928 | 0.9131 | 0.9149 | 0.9136 | 0.9158 | 0.9174 | 0.9162 | 0.9713 | 0.9735 | 0.9719 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0909 | 0.0870 | |
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| 0.0007 | 3.6 | 45000 | 0.1571 | 12.7679 | 0.8907 | 0.8926 | 0.8913 | 0.9118 | 0.9140 | 0.9125 | 0.9146 | 0.9165 | 0.9152 | 0.9724 | 0.9750 | 0.9733 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | |
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| 0.0005 | 4.0 | 50000 | 0.1579 | 12.5795 | 0.8918 | 0.8920 | 0.8915 | 0.9121 | 0.9126 | 0.9120 | 0.9146 | 0.9150 | 0.9144 | 0.9737 | 0.9750 | 0.9739 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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