Hubert Finetuned SAVEE
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: 1.4798 Accuracy: 0.4167
Model source
- Kind
- Other
- File size
- 361 MB
- Base model
- facebook/hubert-base-ls960
- Version
- vRevision 518f9fa
- Updated
- Oct 31, 2026
- Downloads
- 10
- Source
- Hugging Face
Source description
hubert-finetuned-SAVEE
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: 1.4798
- Accuracy: 0.4167
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 |
|---|---|---|---|---|
| No log | 1.0 | 24 | 1.8901 | 0.3125 |
| No log | 2.0 | 48 | 1.7471 | 0.3333 |
| 7.6156 | 3.0 | 72 | 1.5627 | 0.375 |
| 7.6156 | 4.0 | 96 | 1.4798 | 0.4167 |
| 6.7035 | 5.0 | 120 | 1.5339 | 0.3958 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVerified Oct 31
Download files
Repository files
File inventory only; completeness is unverified.
Model artifacts
1 artifact
Model artifacts
1 artifactmodel.safetensors
safetensors · FP32 (unverified) · 361 MB · SHA-256 73747c2375fd…9725 · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- library_name: transformers license: apache-2.0 base_model: facebook/hubert-base-ls960 tags: - generated_from_trainer metrics: - accuracy model-index: - name: hubert-finetuned-SAVEE 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-SAVEE 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: 1.4798 - Accuracy: 0.4167 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 24 | 1.8901 | 0.3125 | | No log | 2.0 | 48 | 1.7471 | 0.3333 | | 7.6156 | 3.0 | 72 | 1.5627 | 0.375 | | 7.6156 | 4.0 | 96 | 1.4798 | 0.4167 | | 6.7035 | 5.0 | 120 | 1.5339 | 0.3958 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 10 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/hubert-finetuned-SAVEE
Source context: 6 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo VasilisAsim/hubert-finetuned-SAVEE
