flan-t5-small-hallucination-text-classification
This model is a fine-tuned version of google/flan-t5-small on the Hallucination Acceptance Agent Instruction dataset. It achieves the following results on the evaluation set:
- Loss: 0.7901
- Precision: 0.7429
- Recall: 0.7450
- F1: 0.7428
- Accuracy: 0.7450
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4967 | 0.4016 | 100 | 0.8049 | 0.7429 | 0.7349 | 0.7248 | 0.7349 |
| 0.4829 | 0.8032 | 200 | 0.7162 | 0.7284 | 0.7319 | 0.7261 | 0.7319 |
| 0.3966 | 1.2048 | 300 | 0.8576 | 0.7526 | 0.7530 | 0.7486 | 0.7530 |
| 0.3115 | 1.6064 | 400 | 0.8358 | 0.7443 | 0.7450 | 0.7438 | 0.7450 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1