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---
language:
- he
base_model: ivrit-ai/whisper-v2-pd1-e1
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: he-cantillation
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# he-cantillation
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.
It achieves the following results on the evaluation set:
- Loss: 0.1065
- Wer: 11.5595
- Avg Precision Exact: 0.9158
- Avg Recall Exact: 0.9153
- Avg F1 Exact: 0.9152
- Avg Precision Letter Shift: 0.9349
- Avg Recall Letter Shift: 0.9345
- Avg F1 Letter Shift: 0.9344
- Avg Precision Word Level: 0.9374
- Avg Recall Word Level: 0.9371
- Avg F1 Word Level: 0.9369
- Avg Precision Word Shift: 0.9744
- Avg Recall Word Shift: 0.9751
- Avg F1 Word Shift: 0.9743
- Precision Median Exact: 1.0
- Recall Median Exact: 1.0
- F1 Median Exact: 1.0
- Precision Max Exact: 1.0
- Recall Max Exact: 1.0
- F1 Max Exact: 1.0
- Precision Min Exact: 0.0
- Recall Min Exact: 0.0
- F1 Min Exact: 0.0
- Precision Min Letter Shift: 0.0
- Recall Min Letter Shift: 0.0
- F1 Min Letter Shift: 0.0
- Precision Min Word Level: 0.0
- Recall Min Word Level: 0.0
- F1 Min Word Level: 0.0
- Precision Min Word Shift: 0.2222
- Recall Min Word Shift: 0.1667
- F1 Min Word Shift: 0.1905
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|
| No log | 8e-05 | 1 | 4.8435 | 119.6859 | 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 |
| 0.1248 | 0.08 | 1000 | 0.1621 | 23.2816 | 0.8165 | 0.8201 | 0.8175 | 0.8444 | 0.8482 | 0.8454 | 0.8487 | 0.8532 | 0.8501 | 0.9200 | 0.9275 | 0.9227 | 0.9 | 0.9 | 0.8966 | 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 | 0.0909 | 0.1111 |
| 0.0907 | 0.16 | 2000 | 0.1268 | 18.2188 | 0.8624 | 0.8589 | 0.8600 | 0.8863 | 0.8828 | 0.8839 | 0.8905 | 0.8869 | 0.8880 | 0.9507 | 0.9495 | 0.9494 | 0.9231 | 0.9167 | 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 | 0.1429 | 0.125 | 0.1333 |
| 0.04 | 0.24 | 3000 | 0.1182 | 14.9446 | 0.8826 | 0.8813 | 0.8815 | 0.9046 | 0.9035 | 0.9035 | 0.9079 | 0.9067 | 0.9068 | 0.9633 | 0.9635 | 0.9628 | 0.9375 | 0.9375 | 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 | 0.125 | 0.1 | 0.1176 |
| 0.0379 | 0.32 | 4000 | 0.1123 | 15.0111 | 0.8839 | 0.8853 | 0.8839 | 0.9081 | 0.9096 | 0.9082 | 0.9110 | 0.9134 | 0.9115 | 0.9615 | 0.9658 | 0.9629 | 0.9333 | 0.9333 | 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 | 0.1 | 0.1 | 0.1176 |
| 0.0274 | 0.4 | 5000 | 0.1092 | 13.3481 | 0.9011 | 0.8989 | 0.8996 | 0.9215 | 0.9194 | 0.9200 | 0.9240 | 0.9225 | 0.9228 | 0.9684 | 0.9685 | 0.9679 | 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 |
| 0.0242 | 0.48 | 6000 | 0.1078 | 13.0044 | 0.9003 | 0.8977 | 0.8985 | 0.9211 | 0.9187 | 0.9194 | 0.9237 | 0.9216 | 0.9221 | 0.9686 | 0.9681 | 0.9678 | 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 |
| 0.0134 | 0.56 | 7000 | 0.1039 | 12.0547 | 0.9086 | 0.9072 | 0.9075 | 0.9270 | 0.9257 | 0.9259 | 0.9299 | 0.9288 | 0.9290 | 0.9699 | 0.9701 | 0.9696 | 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 | 0.1538 | 0.1429 | 0.1538 |
| 0.0118 | 0.64 | 8000 | 0.1077 | 11.8847 | 0.9104 | 0.9110 | 0.9103 | 0.9306 | 0.9313 | 0.9306 | 0.9331 | 0.9339 | 0.9331 | 0.9726 | 0.9748 | 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 | 0.0769 | 0.0909 | 0.0833 |
| 0.0084 | 0.72 | 9000 | 0.1071 | 11.6223 | 0.9145 | 0.9141 | 0.9140 | 0.9336 | 0.9332 | 0.9330 | 0.9358 | 0.9355 | 0.9353 | 0.9742 | 0.9751 | 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 | 0.1 | 0.1176 |
| 0.0065 | 0.8 | 10000 | 0.1065 | 11.5595 | 0.9158 | 0.9153 | 0.9152 | 0.9349 | 0.9345 | 0.9344 | 0.9374 | 0.9371 | 0.9369 | 0.9744 | 0.9751 | 0.9743 | 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 | 0.2222 | 0.1667 | 0.1905 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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