ExHubert-fine-tuned
This model is a fine-tuned version of amiriparian/ExHuBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4376
- Accuracy: 0.8392
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7396 | 1.0 | 64 | 0.7444 | 0.6118 |
0.6937 | 2.0 | 128 | 0.5704 | 0.7647 |
0.4416 | 3.0 | 192 | 0.4876 | 0.8039 |
0.5393 | 4.0 | 256 | 0.4376 | 0.8392 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Downloads last month
- 18
Inference API (serverless) does not yet support model repos that contain custom code.
Model tree for vargha/ExHubert-fine-tuned
Base model
amiriparian/ExHuBERT