checkpoint-291-3ep3bsfrmulti4

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2616
• Recall: 0.9032
• Precision: 0.9655
• F1: 0.9333
• Roc Auc: 0.8333

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: 3
• eval_batch_size: 3
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 291

Training results

Training Loss	Epoch	Step	Validation Loss	Recall	Precision	F1	Roc Auc
0.0	0.33	97	0.1037	0.9677	1.0	0.9836	0.4248
0.0001	1.33	194	0.8674	1.0	0.62	0.7654	0.1087
0.0001	2.33	291	0.2616	0.9032	0.9655	0.9333	0.8333

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.0+cu118
• Datasets 2.17.0
• Tokenizers 0.15.2