roberta-base-kennedy2020constructing

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

• Loss: 0.2110
• Accuracy: 0.9738
• Roc Auc: 0.9915
• Precision: 0.9680
• Recall: 0.9592
• F1: 0.9636

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: 96
• eval_batch_size: 128
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Roc Auc	Precision	Recall	F1
0.2481	1.0	1144	0.2172	0.9001	0.9676	0.9266	0.7861	0.8506
0.1822	2.0	2288	0.1604	0.9380	0.9836	0.9252	0.9017	0.9133
0.1085	3.0	3432	0.1343	0.9575	0.9893	0.9627	0.9180	0.9398
0.0674	4.0	4576	0.1225	0.9649	0.9918	0.9477	0.9558	0.9517
0.0502	5.0	5720	0.1455	0.9688	0.9919	0.9561	0.9576	0.9569
0.0365	6.0	6864	0.1370	0.9698	0.9921	0.9676	0.9481	0.9578
0.0258	7.0	8008	0.1719	0.9706	0.9925	0.9615	0.9570	0.9592
0.0184	8.0	9152	0.1737	0.9731	0.9922	0.9686	0.9567	0.9626
0.0141	9.0	10296	0.2051	0.9734	0.9916	0.9673	0.9588	0.9630
0.01	10.0	11440	0.2110	0.9738	0.9915	0.9680	0.9592	0.9636

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0