---
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