liar_binaryclassifier_roberta_base

This model is a fine-tuned version of roberta-base on the liar dataset. It achieves the following results on the evaluation set:

• Loss: 0.6621
• Model Preparation Time: 0.0069
• Accuracy: 0.5770

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: 3e-06
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Accuracy
0.6934	1.0	461	0.6843	0.0069	0.5553
0.6859	2.0	922	0.6815	0.0069	0.5531
0.6774	3.0	1383	0.6666	0.0069	0.5597
0.6671	4.0	1844	0.6742	0.0069	0.5748
0.6596	5.0	2305	0.6621	0.0069	0.5770

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1