Whisper Small SIT 16 07 26 0457
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: 0.0110 Wer: 0.4639
Fuente del modelo
- Tipo
- Text model
- Tamaño del archivo
- 922 MB
- Modelo base
- Pengwin30/whisper-small-fine-tuned
- Versión
- vFP32
- Actualizado
- 31 oct 2026
- Descargas
- 7
- Fuente
- Hugging Face
Descripción de la fuente
whisper-small-SIT_16_07_26_0457
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: 0.0110
- Wer: 0.4639
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: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7578 | 1.0 | 181 | 0.0262 | 0.8615 |
| 0.0156 | 2.0 | 362 | 0.0132 | 0.3976 |
| 0.0050 | 3.0 | 543 | 0.0070 | 0.3976 |
| 0.0005 | 4.0 | 724 | 0.0110 | 0.4639 |
| 0.0001 | 5.0 | 905 | 0.0110 | 0.4639 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 2.19.0
- Tokenizers 0.22.2
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 31 oct
Download files
Repository files
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Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactomodel.safetensors
safetensors · FP32 (unverified) · 922 MB · SHA-256 340b8f0f4be1…47af · Hugging Face
Download fileExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- library_name: transformers license: mit base_model: Pengwin30/whisper-small-fine-tuned tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-small-SIT_16_07_26_0457 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_16_07_26_0457 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: 0.0110 - Wer: 0.4639 ## 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: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.7578 | 1.0 | 181 | 0.0262 | 0.8615 | | 0.0156 | 2.0 | 362 | 0.0132 | 0.3976 | | 0.0050 | 3.0 | 543 | 0.0070 | 0.3976 | | 0.0005 | 4.0 | 724 | 0.0110 | 0.4639 | | 0.0001 | 5.0 | 905 | 0.0110 | 0.4639 | ### Framework versions - Transformers 5.12.1 - Pytorch 2.11.0+cu128 - Datasets 2.19.0 - Tokenizers 0.22.2
Source context: 7 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo horhh/whisper-small-SIT_16_07_26_0457
Source context: 16 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo horhh/whisper-small-SIT_16_07_26_0457
