| --- |
| library_name: transformers |
| language: |
| - fa |
| license: mit |
| base_model: openai/whisper-large-v3-turbo |
| tags: |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_17_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper-large-v3-turbo-fa - Sadegh Karimi |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 17.0 |
| type: mozilla-foundation/common_voice_17_0 |
| config: fa |
| split: test |
| args: 'config: hi, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 9.627528266117483 |
| --- |
| |
| <!-- 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. --> |
|
|
| # Whisper-large-v3-turbo-fa - Sadegh Karimi |
|
|
| This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 17.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0839 |
| - Wer: 9.6275 |
|
|
| ## 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: 8 |
| - seed: 42 |
| - optimizer: Use 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: 500 |
| - training_steps: 10000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:-----:|:---------------:|:-------:| |
| | 0.1789 | 0.0217 | 500 | 0.2427 | 26.4099 | |
| | 0.2077 | 0.0435 | 1000 | 0.2296 | 27.1873 | |
| | 0.1928 | 0.0652 | 1500 | 0.2320 | 27.5951 | |
| | 0.1801 | 0.0869 | 2000 | 0.2026 | 24.0409 | |
| | 0.1865 | 0.1086 | 2500 | 0.1925 | 22.3742 | |
| | 0.1535 | 0.1304 | 3000 | 0.1872 | 22.9511 | |
| | 0.1463 | 0.1521 | 3500 | 0.1786 | 21.5436 | |
| | 0.0935 | 0.1738 | 4000 | 0.1749 | 20.5330 | |
| | 0.1052 | 0.1956 | 4500 | 0.1597 | 19.0314 | |
| | 0.091 | 0.2173 | 5000 | 0.1553 | 20.2125 | |
| | 0.0743 | 0.2390 | 5500 | 0.1474 | 16.9160 | |
| | 0.096 | 0.2607 | 6000 | 0.1352 | 15.9027 | |
| | 0.111 | 0.2825 | 6500 | 0.1259 | 14.9071 | |
| | 0.089 | 0.3042 | 7000 | 0.1179 | 14.1146 | |
| | 0.0813 | 0.3259 | 7500 | 0.1101 | 12.8653 | |
| | 0.072 | 0.3477 | 8000 | 0.1012 | 11.8138 | |
| | 0.0715 | 0.3694 | 8500 | 0.0948 | 10.9791 | |
| | 0.0683 | 0.3911 | 9000 | 0.0903 | 10.2563 | |
| | 0.0634 | 0.4128 | 9500 | 0.0861 | 9.6616 | |
| | 0.0739 | 0.4346 | 10000 | 0.0839 | 9.6275 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.1 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
