Hubert Finetuned Expresso
This model is a fine-tuned version of facebook/hubert-base-ls960 on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.2814 Accuracy: 0.9297
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 361 MB
- Modelo base
- facebook/hubert-base-ls960
- Versión
- vRevision 15b020a
- Actualizado
- 25 oct 2026
- Descargas
- 8
- Fuente
- Hugging Face
Descripción de la fuente
hubert-finetuned-Expresso
This model is a fine-tuned version of facebook/hubert-base-ls960 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2814
- Accuracy: 0.9297
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.4413 | 1.0 | 581 | 0.6025 | 0.8361 |
| 2.2079 | 2.0 | 1162 | 0.4785 | 0.8482 |
| 1.7536 | 3.0 | 1743 | 0.5244 | 0.8366 |
| 1.1475 | 4.0 | 2324 | 0.3140 | 0.9150 |
| 0.9236 | 5.0 | 2905 | 0.2814 | 0.9297 |
Framework versions
- Transformers 5.10.2
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 25 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- library_name: transformers license: apache-2.0 base_model: facebook/hubert-base-ls960 tags: - generated_from_trainer metrics: - accuracy model-index: - name: hubert-finetuned-Expresso 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. --> # hubert-finetuned-Expresso This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2814 - Accuracy: 0.9297 ## 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: 3e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - 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: 0.1 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 3.4413 | 1.0 | 581 | 0.6025 | 0.8361 | | 2.2079 | 2.0 | 1162 | 0.4785 | 0.8482 | | 1.7536 | 3.0 | 1743 | 0.5244 | 0.8366 | | 1.1475 | 4.0 | 2324 | 0.3140 | 0.9150 | | 0.9236 | 5.0 | 2905 | 0.2814 | 0.9297 | ### Framework versions - Transformers 5.10.2 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 8 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/hubert-finetuned-Expresso
Source context: 6 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/hubert-finetuned-Expresso
