roberta-base-bne-finetuned-detests-wandb

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: 0.3838
• Accuracy: 0.8543
• F1-score: 0.7832
• Precision: 0.7983
• Recall: 0.7712
• Auc: 0.7712

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
0.3307	1.0	87	0.3771	0.8560	0.7659	0.8224	0.7367	0.7367
0.1068	2.0	174	0.3838	0.8543	0.7832	0.7983	0.7712	0.7712

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0