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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: 0.0811
- Wer: 8.3294
- Avg Precision Exact: 0.9316
- Avg Recall Exact: 0.9306
- Avg F1 Exact: 0.9308
- Avg Precision Letter Shift: 0.9429
- Avg Recall Letter Shift: 0.9420
- Avg F1 Letter Shift: 0.9421
- Avg Precision Word Level: 0.9449
- Avg Recall Word Level: 0.9440
- Avg F1 Word Level: 0.9441
- Avg Precision Word Shift: 0.9733
- Avg Recall Word Shift: 0.9727
- Avg F1 Word Shift: 0.9726
- 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: 0.1429
- Recall Min Word Shift: 0.125
- F1 Min Word Shift: 0.1333
## 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: 30000
- 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 | 5.0569 | 117.7539 | 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 |
| 0.0574 | 0.2584 | 5000 | 0.1118 | 15.1956 | 0.8739 | 0.8737 | 0.8732 | 0.8937 | 0.8935 | 0.8931 | 0.8968 | 0.8969 | 0.8963 | 0.9461 | 0.9483 | 0.9466 | 0.9286 | 0.9231 | 0.9333 | 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 |
| 0.0305 | 0.5167 | 10000 | 0.0953 | 11.9985 | 0.8991 | 0.8996 | 0.8989 | 0.9138 | 0.9146 | 0.9137 | 0.9165 | 0.9178 | 0.9167 | 0.9563 | 0.9591 | 0.9571 | 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 | 0.125 | 0.1333 |
| 0.0185 | 0.7751 | 15000 | 0.0868 | 10.8122 | 0.9110 | 0.9117 | 0.9110 | 0.9265 | 0.9273 | 0.9265 | 0.9291 | 0.9301 | 0.9291 | 0.9629 | 0.9645 | 0.9632 | 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 |
| 0.0126 | 1.0334 | 20000 | 0.0848 | 9.5283 | 0.9168 | 0.9163 | 0.9162 | 0.9298 | 0.9294 | 0.9292 | 0.9321 | 0.9316 | 0.9315 | 0.9672 | 0.9670 | 0.9666 | 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 |
| 0.0061 | 1.2918 | 25000 | 0.0850 | 8.8801 | 0.9244 | 0.9266 | 0.9251 | 0.9358 | 0.9381 | 0.9366 | 0.9381 | 0.9403 | 0.9388 | 0.9686 | 0.9706 | 0.9691 | 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 |
| 0.0069 | 1.5501 | 30000 | 0.0811 | 8.3294 | 0.9316 | 0.9306 | 0.9308 | 0.9429 | 0.9420 | 0.9421 | 0.9449 | 0.9440 | 0.9441 | 0.9733 | 0.9727 | 0.9726 | 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 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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