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This model is a fine-tuned version of Pengwin30/whisper-small-fine-tuned on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.0369 Wer: 1.3254
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This model is a fine-tuned version of Pengwin30/whisper-small-fine-tuned on an unknown dataset. It achieves the following results on the evaluation set:
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1 sourceVerified Sep 22
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7852 | 1.0 | 181 | 0.0441 | 2.3857 |
| 0.0298 | 2.0 | 362 | 0.0421 | 2.1206 |
| 0.0059 | 3.0 | 543 | 0.0369 | 1.3254 |
--- library_name: transformers license: mit base_model: Pengwin30/whisper-small-fine-tuned tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-small-SIT_08_07_26_0521 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. --> # whisper-small-SIT_08_07_26_0521 This model is a fine-tuned version of [Pengwin30/whisper-small-fine-tuned](https://huggingface.co/Pengwin30/whisper-small-fine-tuned) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0369 - Wer: 1.3254 ## 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: 8 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.7852 | 1.0 | 181 | 0.0441 | 2.3857 | | 0.0298 | 2.0 | 362 | 0.0421 | 2.1206 | | 0.0059 | 3.0 | 543 | 0.0369 | 1.3254 | ### Framework versions - Transformers 5.12.1 - Pytorch 2.11.0+cu128 - Datasets 2.19.0 - Tokenizers 0.22.2
Source context: 3 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo horhh/whisper-small-SIT_08_07_26_0521
