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---
library_name: transformers
language:
- he
license: mit
base_model: distil-whisper/distil-large-v3.5
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 [distil-whisper/distil-large-v3.5](https://huggingface.co/distil-whisper/distil-large-v3.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7945
- Wer: 68.9512
- Avg Precision Exact: 0.2622
- Avg Recall Exact: 0.2502
- Avg F1 Exact: 0.2513
- Avg Precision Letter Shift: 0.2922
- Avg Recall Letter Shift: 0.2803
- Avg F1 Letter Shift: 0.2796
- Avg Precision Word Level: 0.3129
- Avg Recall Word Level: 0.3458
- Avg F1 Word Level: 0.3227
- Avg Precision Word Shift: 0.5277
- Avg Recall Word Shift: 0.5512
- Avg F1 Word Shift: 0.5260
- Precision Median Exact: 0.1429
- Recall Median Exact: 0.1379
- F1 Median Exact: 0.1333
- 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: 0.0
- Recall Min Word Shift: 0.0
- F1 Min Word Shift: 0.0
## 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: 16
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- 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 | 0.0001 | 1 | 12.1921 | 169.3043 | 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 |
| 0.096 | 0.5925 | 5000 | 0.9503 | 76.8918 | 0.1974 | 0.2042 | 0.1981 | 0.2302 | 0.2405 | 0.2312 | 0.2519 | 0.2806 | 0.2607 | 0.4684 | 0.5193 | 0.4828 | 0.1071 | 0.1111 | 0.1053 | 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 |
| 0.0614 | 1.1850 | 10000 | 0.7945 | 68.9512 | 0.2622 | 0.2502 | 0.2513 | 0.2922 | 0.2803 | 0.2796 | 0.3129 | 0.3458 | 0.3227 | 0.5277 | 0.5512 | 0.5260 | 0.1429 | 0.1379 | 0.1333 | 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 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.7.0+cu126
- Datasets 2.12.0
- Tokenizers 0.20.1
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