library_name: transformers
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics: - accuracy
model-index: - name: electra-base-discriminator-disaster-tweet-jailbreaking
results: []
electra-base-discriminator-disaster-tweet-jailbreaking
This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5879
- Accuracy: 0.7258
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 50
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5828 | 1.0 | 243 | 0.7508 | 0.6268 |
| 0.5214 | 2.0 | 486 | 0.6171 | 0.6433 |
| 0.5550 | 3.0 | 729 | 0.5942 | 0.7278 |
| 0.4006 | 4.0 | 972 | 0.5865 | 0.7258 |
| 0.3184 | 5.0 | 1215 | 0.6823 | 0.7196 |
| 0.1803 | 6.0 | 1458 | 0.8771 | 0.7175 |
| 0.1859 | 7.0 | 1701 | 0.9165 | 0.7216 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2