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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: 0.1099 |
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- Wer: 16.2686 |
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- Avg Precision Exact: 0.8645 |
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- Avg Recall Exact: 0.8618 |
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- Avg F1 Exact: 0.8626 |
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- Avg Precision Letter Shift: 0.8838 |
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- Avg Recall Letter Shift: 0.8813 |
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- Avg F1 Letter Shift: 0.8819 |
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- Avg Precision Word Level: 0.8869 |
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- Avg Recall Word Level: 0.8850 |
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- Avg F1 Word Level: 0.8853 |
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- Avg Precision Word Shift: 0.9412 |
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- Avg Recall Word Shift: 0.9408 |
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- Avg F1 Word Shift: 0.9403 |
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- Precision Median Exact: 0.9231 |
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- Recall Median Exact: 0.9231 |
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- F1 Median Exact: 0.9286 |
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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: 0.0909 |
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- F1 Min Word Shift: 0.1111 |
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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: 10 |
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- training_steps: 3000 |
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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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| 0.1552 | 0.0517 | 1000 | 0.1843 | 26.9266 | 0.7790 | 0.7668 | 0.7718 | 0.8099 | 0.7974 | 0.8025 | 0.8153 | 0.8044 | 0.8088 | 0.8935 | 0.8895 | 0.8902 | 0.8462 | 0.8462 | 0.8462 | 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 | 0.0909 | 0.1111 | |
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| 0.0973 | 0.1033 | 2000 | 0.1317 | 19.9251 | 0.8323 | 0.8338 | 0.8323 | 0.8540 | 0.8558 | 0.8542 | 0.8583 | 0.8605 | 0.8587 | 0.9204 | 0.9258 | 0.9223 | 0.9091 | 0.9091 | 0.9091 | 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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| 0.0625 | 0.1550 | 3000 | 0.1099 | 16.2686 | 0.8645 | 0.8618 | 0.8626 | 0.8838 | 0.8813 | 0.8819 | 0.8869 | 0.8850 | 0.8853 | 0.9412 | 0.9408 | 0.9403 | 0.9231 | 0.9231 | 0.9286 | 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 | 0.0909 | 0.1111 | |
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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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