metadata
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta_Energie
results: []
deberta_Energie
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0142
- Accuracy: 0.9913
- F1: 0.9913
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.4003 | 1.0 | 116 | 0.9262 | 0.6524 | 0.6025 |
| 0.7697 | 2.0 | 232 | 0.3836 | 0.8906 | 0.8899 |
| 0.3904 | 3.0 | 348 | 0.2468 | 0.9256 | 0.9191 |
| 0.2749 | 4.0 | 464 | 0.2202 | 0.9324 | 0.9283 |
| 0.2043 | 5.0 | 580 | 0.1122 | 0.9672 | 0.9673 |
| 0.1808 | 6.0 | 696 | 0.1004 | 0.9701 | 0.9706 |
| 0.1274 | 7.0 | 812 | 0.0822 | 0.9745 | 0.9747 |
| 0.1018 | 8.0 | 928 | 0.0673 | 0.9791 | 0.9794 |
| 0.0711 | 9.0 | 1044 | 0.0457 | 0.9870 | 0.9870 |
| 0.0609 | 10.0 | 1160 | 0.0370 | 0.9867 | 0.9867 |
| 0.0594 | 11.0 | 1276 | 0.0240 | 0.9886 | 0.9886 |
| 0.0332 | 12.0 | 1392 | 0.0182 | 0.9913 | 0.9913 |
| 0.0278 | 13.0 | 1508 | 0.0183 | 0.9908 | 0.9908 |
| 0.0281 | 14.0 | 1624 | 0.0142 | 0.9913 | 0.9913 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0