metadata
library_name: transformers
license: apache-2.0
base_model: markusbayer/CySecBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: cysecbert-ttp
results: []
cysecbert-ttp
This model is a fine-tuned version of markusbayer/CySecBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0182
- F1 Micro: 0.3613
- F1 Macro: 0.0811
- Precision: 0.7753
- Recall: 0.2355
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0359 | 1.0 | 1226 | 0.0316 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0278 | 2.0 | 2452 | 0.0278 | 0.0202 | 0.0036 | 0.8571 | 0.0102 |
| 0.0242 | 3.0 | 3678 | 0.0230 | 0.2709 | 0.0438 | 0.7462 | 0.1655 |
| 0.0233 | 4.0 | 4904 | 0.0193 | 0.2881 | 0.0567 | 0.8361 | 0.1741 |
| 0.0186 | 5.0 | 6130 | 0.0182 | 0.3613 | 0.0811 | 0.7753 | 0.2355 |
Framework versions
- Transformers 4.57.5
- Pytorch 2.2.0
- Datasets 4.5.0
- Tokenizers 0.22.2