Downloads · 30 days
3
9% of all-time downloads
results_v2.2
haval995/results_v2.2
results_v2.2 is a text classification model from haval995. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
33
Public
Parameters
125M
499 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors499 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- May 6, 2026
- Updated
- May 6, 2026
- SHA
- b8d16a81
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
results_v2.2
This model is a fine-tuned version of haval995/roberta-large-causal-hallucination-detector_V_2.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4622
- Accuracy: 0.8696
- F1 Macro: 0.8460
- F1 Supported: 0.7857
- Recall Supported: 1.0
- F1 Hallucination: 0.9062
- Recall Hallucination: 0.8286
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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_steps: 0.1
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Supported | Recall Supported | F1 Hallucination | Recall Hallucination |
|---|---|---|---|---|---|---|---|---|---|
| 0.6675 | 1.0 | 54 | 0.3172 | 0.9338 | 0.9334 | 0.9286 | 0.9848 | 0.9383 | 0.8941 |
| 0.5336 | 2.0 | 108 | 0.3151 | 0.9404 | 0.9395 | 0.9323 | 0.9394 | 0.9467 | 0.9412 |
| 0.5047 | 3.0 | 162 | 0.3452 | 0.9470 | 0.9466 | 0.9420 | 0.9848 | 0.9512 | 0.9176 |
| 0.4754 | 4.0 | 216 | 0.3812 | 0.9205 | 0.9202 | 0.9155 | 0.9848 | 0.925 | 0.8706 |
| 0.4676 | 5.0 | 270 | 0.3236 | 0.9470 | 0.9465 | 0.9412 | 0.9697 | 0.9518 | 0.9294 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- May 6, 2026
- Updated
- May 6, 2026