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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-large-v2 |
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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-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0963 |
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- Wer: 7.5207 |
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- Avg Precision Exact: 0.9345 |
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- Avg Recall Exact: 0.9347 |
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- Avg F1 Exact: 0.9343 |
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- Avg Precision Letter Shift: 0.9448 |
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- Avg Recall Letter Shift: 0.9451 |
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- Avg F1 Letter Shift: 0.9447 |
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- Avg Precision Word Level: 0.9467 |
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- Avg Recall Word Level: 0.9470 |
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- Avg F1 Word Level: 0.9466 |
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- Avg Precision Word Shift: 0.9749 |
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- Avg Recall Word Shift: 0.9755 |
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- Avg F1 Word Shift: 0.9748 |
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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: 0.1333 |
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- Recall Min Word Shift: 0.1111 |
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- F1 Min Word Shift: 0.125 |
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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: 500 |
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- training_steps: 80000 |
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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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| No log | 0.0001 | 1 | 5.8251 | 118.7797 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
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| 0.0424 | 0.5167 | 10000 | 0.1027 | 13.0873 | 0.8913 | 0.8931 | 0.8917 | 0.9070 | 0.9088 | 0.9074 | 0.9103 | 0.9117 | 0.9105 | 0.9544 | 0.9564 | 0.9548 | 0.9412 | 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 | 0.125 | 0.1333 | |
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| 0.0139 | 1.0334 | 20000 | 0.0944 | 10.6171 | 0.9121 | 0.9101 | 0.9107 | 0.9250 | 0.9231 | 0.9236 | 0.9271 | 0.9256 | 0.9260 | 0.9644 | 0.9639 | 0.9637 | 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 | 0.0 | 0.0 | 0.0 | |
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| 0.0085 | 1.5501 | 30000 | 0.0906 | 9.6951 | 0.9196 | 0.9190 | 0.9189 | 0.9328 | 0.9324 | 0.9322 | 0.9353 | 0.9351 | 0.9348 | 0.9679 | 0.9687 | 0.9679 | 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 | 0.0 | 0.0 | 0.0 | |
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| 0.0038 | 2.0668 | 40000 | 0.0954 | 9.0311 | 0.9217 | 0.9201 | 0.9206 | 0.9331 | 0.9316 | 0.9320 | 0.9352 | 0.9335 | 0.9340 | 0.9696 | 0.9696 | 0.9692 | 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 | 0.1111 | 0.125 | |
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| 0.0033 | 2.5834 | 50000 | 0.0927 | 8.4962 | 0.9258 | 0.9256 | 0.9254 | 0.9371 | 0.9370 | 0.9367 | 0.9391 | 0.9392 | 0.9388 | 0.9718 | 0.9729 | 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 | 0.1429 | 0.125 | 0.1333 | |
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| 0.0025 | 3.1001 | 60000 | 0.0928 | 7.9801 | 0.9305 | 0.9299 | 0.9298 | 0.9413 | 0.9407 | 0.9407 | 0.9435 | 0.9429 | 0.9429 | 0.9744 | 0.9747 | 0.9742 | 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 | 0.1111 | 0.125 | |
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| 0.0012 | 3.6168 | 70000 | 0.0960 | 7.9738 | 0.9312 | 0.9305 | 0.9306 | 0.9421 | 0.9415 | 0.9416 | 0.9441 | 0.9437 | 0.9436 | 0.9737 | 0.9739 | 0.9734 | 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 | 0.1333 | 0.1111 | 0.125 | |
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| 0.0002 | 4.1335 | 80000 | 0.0963 | 7.5207 | 0.9345 | 0.9347 | 0.9343 | 0.9448 | 0.9451 | 0.9447 | 0.9467 | 0.9470 | 0.9466 | 0.9749 | 0.9755 | 0.9748 | 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 | 0.1333 | 0.1111 | 0.125 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.2.1 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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