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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

ArtOtherBasismodellfacebook/hubert-base-ls960VersionRevision 15b020aBBewertung

Modellquelle

Art
Other
Dateigröße
361 MB
Basismodell
facebook/hubert-base-ls960
Version
vRevision 15b020a
Aktualisiert
25. Okt. 2026
Downloads
8
Quelle
Hugging Face

Quellenbeschreibung

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 LossEpochStepValidation LossAccuracy
3.44131.05810.60250.8361
2.20792.011620.47850.8482
1.75363.017430.52440.8366
1.14754.023240.31400.9150
0.92365.029050.28140.9297

Framework versions

  • Transformers 5.10.2
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Quellen

1 Quelle
Hugging FacePrimärVersion 15b020a4c7996d9eea1cceda531a09c5fb75362a
huggingface.co/VasilisAsim/hubert-finetuned-Expresso/tree/15b020a4c7996d9eea1cceda531a09c5fb75362a

Verifiziert 25. Okt.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 361 MB · SHA-256 494fcf343ca0…0f0d · Hugging Face

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Quellenauszüge

3 Auszüge

--- 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