| --- |
| 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: 8.5391 |
| - Wer: 100.0 |
| - Avg Precision Exact: 0.0025 |
| - Avg Recall Exact: 0.0108 |
| - Avg F1 Exact: 0.0040 |
| - Avg Precision Letter Shift: 0.0838 |
| - Avg Recall Letter Shift: 0.0277 |
| - Avg F1 Letter Shift: 0.0417 |
| - Avg Precision Word Level: 0.0118 |
| - Avg Recall Word Level: 0.0511 |
| - Avg F1 Word Level: 0.0190 |
| - Avg Precision Word Shift: 0.1441 |
| - Avg Recall Word Shift: 0.0917 |
| - Avg F1 Word Shift: 0.1042 |
| - Precision Median Exact: 0.0 |
| - Recall Median Exact: 0.0 |
| - F1 Median Exact: 0.0 |
| - Precision Max Exact: 0.0769 |
| - Recall Max Exact: 0.3333 |
| - F1 Max Exact: 0.125 |
| - 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-06 |
| - 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: 20 |
| - training_steps: 5 |
| - 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 | 0.0040 | 1 | 8.5391 | 100.0 | 0.0025 | 0.0108 | 0.0040 | 0.0838 | 0.0277 | 0.0417 | 0.0118 | 0.0511 | 0.0190 | 0.1441 | 0.0917 | 0.1042 | 0.0 | 0.0 | 0.0 | 0.0769 | 0.3333 | 0.125 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| | No log | 0.0202 | 5 | 8.5391 | 100.0 | 0.0025 | 0.0108 | 0.0040 | 0.0838 | 0.0277 | 0.0417 | 0.0118 | 0.0511 | 0.0190 | 0.1441 | 0.0917 | 0.1042 | 0.0 | 0.0 | 0.0 | 0.0769 | 0.3333 | 0.125 | 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 4.41.2 |
| - Pytorch 2.2.1 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
