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metadata
license: apache-2.0
base_model: google/flan-t5-small
tags:
  - generated_from_trainer
  - hallucination
  - hallucination-classification
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: custom-flan-t5-small-hallucination-classification
    results: []
language:
  - en

custom-flan-t5-small-hallucination-classification

This model is a fine-tuned version of google/flan-t5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6832
  • Precision: 0.7473
  • Recall: 0.7470
  • F1: 0.7393
  • Accuracy: 0.7470

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: 3

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.9007 0.4016 100 0.8154 0.6926 0.6596 0.6202 0.6596
0.7915 0.8032 200 0.7602 0.7181 0.6867 0.6585 0.6867
0.7089 1.2048 300 0.6769 0.7323 0.7329 0.7250 0.7329
0.6381 1.6064 400 0.6954 0.7338 0.7329 0.7240 0.7329
0.6528 2.0080 500 0.6510 0.7423 0.7410 0.7318 0.7410
0.5652 2.4096 600 0.6856 0.7340 0.7339 0.7303 0.7339
0.5446 2.8112 700 0.6832 0.7473 0.7470 0.7393 0.7470

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1