| ---
|
| library_name: transformers
|
| language:
|
| - th
|
| license: apache-2.0
|
| base_model: openai/whisper-small
|
| tags:
|
| - generated_from_trainer
|
| datasets:
|
| - fsicoli/common_voice_22_0
|
| metrics:
|
| - wer
|
| model-index:
|
| - name: Whisper Small Th - Testhai
|
| results:
|
| - task:
|
| name: Automatic Speech Recognition
|
| type: automatic-speech-recognition
|
| dataset:
|
| name: Common Voice 22.0
|
| type: fsicoli/common_voice_22_0
|
| config: th
|
| split: test[:2%]
|
| args: 'config: th, split: test'
|
| metrics:
|
| - name: Wer
|
| type: wer
|
| value: 100.0
|
| ---
|
|
|
| <!-- 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 Small Th - Testhai
|
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 22.0 dataset.
|
| It achieves the following results on the evaluation set:
|
| - Loss: 2.9453
|
| - Wer: 100.0
|
|
|
| ## 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: 0.001
|
| - train_batch_size: 2
|
| - eval_batch_size: 1
|
| - seed: 42
|
| - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
| - lr_scheduler_type: linear
|
| - num_epochs: 3
|
| - mixed_precision_training: Native AMP
|
|
|
| ### Training results
|
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer |
|
| |:-------------:|:-----:|:----:|:---------------:|:-----:|
|
| | 3.3587 | 1.0 | 330 | 3.2810 | 100.0 |
|
| | 2.2188 | 2.0 | 660 | 3.0993 | 100.0 |
|
| | 2.4391 | 3.0 | 990 | 2.9453 | 100.0 |
|
|
|
|
|
| ### Framework versions
|
|
|
| - Transformers 5.9.0
|
| - Pytorch 2.12.0+cu132
|
| - Datasets 4.8.5
|
| - Tokenizers 0.22.2
|
| |
