xlm-roberta-base-finetuned-detests-wandb24

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

• Loss: 0.4371
• Accuracy: 0.7938
• F1-score: 0.7241
• Precision: 0.7136
• Recall: 0.7396
• Auc: 0.7396

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: 16
• eval_batch_size: 16
• 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
0.458	1.0	153	0.4512	0.7725	0.4358	0.3863	0.5	0.5
0.4262	2.0	306	0.4371	0.7938	0.7241	0.7136	0.7396	0.7396

Framework versions

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