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---
language:
- he
license: apache-2.0
base_model: openai/whisper-large-v2
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 [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0963
- Wer: 7.5207
- Avg Precision Exact: 0.9345
- Avg Recall Exact: 0.9347
- Avg F1 Exact: 0.9343
- Avg Precision Letter Shift: 0.9448
- Avg Recall Letter Shift: 0.9451
- Avg F1 Letter Shift: 0.9447
- Avg Precision Word Level: 0.9467
- Avg Recall Word Level: 0.9470
- Avg F1 Word Level: 0.9466
- Avg Precision Word Shift: 0.9749
- Avg Recall Word Shift: 0.9755
- Avg F1 Word Shift: 0.9748
- 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: 0.1333
- Recall Min Word Shift: 0.1111
- F1 Min Word Shift: 0.125
## 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: 500
- training_steps: 80000
- 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 | 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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