roberta-base-bne-finetuned-detests-wandb24

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

• Loss: 0.3730
• Accuracy: 0.8592
• F1-score: 0.7922
• Precision: 0.8046
• Recall: 0.7820
• Auc: 0.7820

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• 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	Accuracy	F1-score	Precision	Recall	Auc
0.344	1.0	77	0.3268	0.8642	0.7814	0.8347	0.7522	0.7522
0.1996	2.0	154	0.3730	0.8592	0.7922	0.8046	0.7820	0.7820

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.1