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--- |
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language: |
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- he |
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base_model: ivrit-ai/whisper-v2-pd1-e1 |
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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 [ivrit-ai/whisper-v2-pd1-e1](https://huggingface.co/ivrit-ai/whisper-v2-pd1-e1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0952 |
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- Wer: 7.8511 |
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- Avg Precision Exact: 0.9335 |
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- Avg Recall Exact: 0.9352 |
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- Avg F1 Exact: 0.9340 |
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- Avg Precision Letter Shift: 0.9440 |
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- Avg Recall Letter Shift: 0.9458 |
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- Avg F1 Letter Shift: 0.9446 |
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- Avg Precision Word Level: 0.9462 |
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- Avg Recall Word Level: 0.9479 |
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- Avg F1 Word Level: 0.9467 |
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- Avg Precision Word Shift: 0.9714 |
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- Avg Recall Word Shift: 0.9736 |
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- Avg F1 Word Shift: 0.9721 |
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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: 0.125 |
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- F1 Min Word Shift: 0.1333 |
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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 | 5.0835 | 121.5079 | 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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| 0.0423 | 0.5167 | 10000 | 0.1010 | 13.7858 | 0.8705 | 0.8797 | 0.8745 | 0.8866 | 0.8961 | 0.8908 | 0.8899 | 0.8991 | 0.8939 | 0.9426 | 0.9519 | 0.9466 | 0.9286 | 0.9412 | 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 | 0.0 | 0.0 | 0.0 | |
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| 0.0139 | 1.0334 | 20000 | 0.0950 | 10.6832 | 0.9090 | 0.9076 | 0.9079 | 0.9219 | 0.9205 | 0.9208 | 0.9251 | 0.9237 | 0.9239 | 0.9610 | 0.9611 | 0.9605 | 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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| 0.0089 | 1.5501 | 30000 | 0.0914 | 10.2458 | 0.9091 | 0.9077 | 0.9081 | 0.9208 | 0.9196 | 0.9198 | 0.9231 | 0.9220 | 0.9222 | 0.9596 | 0.9590 | 0.9589 | 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 | 0.1 | 0.125 | 0.1111 | |
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| 0.0032 | 2.0668 | 40000 | 0.0922 | 9.3269 | 0.9163 | 0.9159 | 0.9157 | 0.9282 | 0.9279 | 0.9277 | 0.9307 | 0.9303 | 0.9301 | 0.9666 | 0.9676 | 0.9667 | 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 | 0.0909 | 0.1111 | 0.1176 | |
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| 0.0025 | 2.5834 | 50000 | 0.0924 | 9.0500 | 0.9171 | 0.9179 | 0.9172 | 0.9283 | 0.9292 | 0.9284 | 0.9307 | 0.9314 | 0.9307 | 0.9656 | 0.9669 | 0.9659 | 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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| 0.0022 | 3.1001 | 60000 | 0.0933 | 8.3137 | 0.9272 | 0.9266 | 0.9266 | 0.9377 | 0.9371 | 0.9371 | 0.9399 | 0.9393 | 0.9393 | 0.9702 | 0.9702 | 0.9698 | 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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| 0.0006 | 3.6168 | 70000 | 0.0947 | 8.0682 | 0.9287 | 0.9302 | 0.9291 | 0.9393 | 0.9409 | 0.9398 | 0.9417 | 0.9430 | 0.9420 | 0.9706 | 0.9723 | 0.9710 | 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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| 0.0002 | 4.1335 | 80000 | 0.0952 | 7.8511 | 0.9335 | 0.9352 | 0.9340 | 0.9440 | 0.9458 | 0.9446 | 0.9462 | 0.9479 | 0.9467 | 0.9714 | 0.9736 | 0.9721 | 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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### 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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