|
|
--- |
|
|
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 |
|
|
|
