xlm-roberta-base-finetuned-detests-wandb

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: 0.4658
• Accuracy: 0.8232
• F1-score: 0.7604
• Precision: 0.7501
• Recall: 0.7739
• Auc: 0.7739

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
0.4464	1.0	174	0.4631	0.8118	0.7509	0.7377	0.7716	0.7716
0.2623	2.0	348	0.4658	0.8232	0.7604	0.7501	0.7739	0.7739

Framework versions

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