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---
library_name: transformers
language:
- he
license: apache-2.0
base_model: openai/whisper-tiny
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-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9273
- Wer: 71.8937
- Avg Precision Exact: 0.1966
- Avg Recall Exact: 0.2113
- Avg F1 Exact: 0.2010
- Avg Precision Letter Shift: 0.2269
- Avg Recall Letter Shift: 0.2498
- Avg F1 Letter Shift: 0.2336
- Avg Precision Word Level: 0.2459
- Avg Recall Word Level: 0.2741
- Avg F1 Word Level: 0.2538
- Avg Precision Word Shift: 0.4328
- Avg Recall Word Shift: 0.5013
- Avg F1 Word Shift: 0.4529
- Precision Median Exact: 0.0638
- Recall Median Exact: 0.0870
- F1 Median Exact: 0.0723
- 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: 1000
- training_steps: 100000
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|
| 0.0506 | 3.5549 | 30000 | 0.7696 | 74.5620 | 0.1888 | 0.1999 | 0.1925 | 0.2219 | 0.2382 | 0.2266 | 0.2426 | 0.2636 | 0.2485 | 0.4348 | 0.4847 | 0.4502 | 0.0714 | 0.0854 | 0.0755 | 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 |
| 0.0214 | 7.1098 | 60000 | 0.8339 | 70.3940 | 0.2052 | 0.2197 | 0.2098 | 0.2364 | 0.2572 | 0.2429 | 0.2575 | 0.2825 | 0.2647 | 0.4499 | 0.5098 | 0.4678 | 0.0741 | 0.0930 | 0.08 | 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 |
| 0.0062 | 10.6648 | 90000 | 0.9273 | 71.8937 | 0.1966 | 0.2113 | 0.2010 | 0.2269 | 0.2498 | 0.2336 | 0.2459 | 0.2741 | 0.2538 | 0.4328 | 0.5013 | 0.4529 | 0.0638 | 0.0870 | 0.0723 | 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 2.6.0+cu126
- Datasets 2.12.0
- Tokenizers 0.20.1
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