roberta-base_legal_nli_finetuned

This model is a fine-tuned version of FacebookAI/roberta-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.7710
• Accuracy: 0.8298
• Precision: 0.8442
• Recall: 0.8324
• F1: 0.8363

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	28	1.0979	0.3085	0.1028	0.3333	0.1572
No log	2.0	56	1.0881	0.3085	0.1028	0.3333	0.1572
No log	3.0	84	0.4565	0.8404	0.8412	0.8437	0.8423
No log	4.0	112	0.4155	0.8617	0.8651	0.8652	0.8650
No log	5.0	140	0.5513	0.8085	0.8386	0.8130	0.8167
No log	6.0	168	0.6108	0.8723	0.8783	0.8750	0.8765
No log	7.0	196	0.6971	0.8298	0.8442	0.8324	0.8363
No log	8.0	224	0.6893	0.8298	0.8442	0.8324	0.8363
No log	9.0	252	0.7855	0.8298	0.8442	0.8324	0.8363
No log	10.0	280	0.7710	0.8298	0.8442	0.8324	0.8363

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0
• Datasets 2.21.0
• Tokenizers 0.19.1