metadata
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: polar4
results: []
polar4
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5187
- Accuracy: 0.7426
- F1: 0.7199
- Precision: 0.7477
- Recall: 0.7426
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: 0.0002
- train_batch_size: 200
- eval_batch_size: 200
- seed: 42
- 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_ratio: 0.2
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6359 | 7.6923 | 100 | 0.6229 | 0.6357 | 0.4941 | 0.4041 | 0.6357 |
| 0.5953 | 15.3846 | 200 | 0.5654 | 0.7039 | 0.6698 | 0.7030 | 0.7039 |
| 0.5605 | 23.0769 | 300 | 0.5510 | 0.6930 | 0.6297 | 0.7259 | 0.6930 |
| 0.5578 | 30.7692 | 400 | 0.5273 | 0.7426 | 0.7384 | 0.7376 | 0.7426 |
| 0.5635 | 38.4615 | 500 | 0.5198 | 0.7364 | 0.7257 | 0.7301 | 0.7364 |
| 0.5443 | 46.1538 | 600 | 0.5214 | 0.7271 | 0.6978 | 0.7338 | 0.7271 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1