Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use leomaurodesenv/roberta-base-trustairlab-jailbreak with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leomaurodesenv/roberta-base-trustairlab-jailbreak with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leomaurodesenv/roberta-base-trustairlab-jailbreak")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leomaurodesenv/roberta-base-trustairlab-jailbreak") model = AutoModelForSequenceClassification.from_pretrained("leomaurodesenv/roberta-base-trustairlab-jailbreak", device_map="auto") - Notebooks
- Google Colab
- Kaggle
roberta-base-trustairlab-jailbreak
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2034
- Accuracy: 0.9350
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.2829 | 1.0 | 605 | 0.2366 | 0.9375 |
| 0.1576 | 2.0 | 1210 | 0.2326 | 0.9408 |
| 0.2414 | 3.0 | 1815 | 0.2352 | 0.9412 |
| 0.1549 | 4.0 | 2420 | 0.2033 | 0.9342 |
| 0.1124 | 5.0 | 3025 | 0.2990 | 0.9384 |
| 0.0571 | 6.0 | 3630 | 0.2484 | 0.9425 |
| 0.2514 | 7.0 | 4235 | 0.3064 | 0.9392 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2
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Model tree for leomaurodesenv/roberta-base-trustairlab-jailbreak
Base model
FacebookAI/roberta-base