results

This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1381
• Accuracy: 0.9541
• F1: 0.9541

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.1876	1.0	1399	0.1381	0.9541	0.9541
0.1279	2.0	2798	0.1588	0.9609	0.9609
0.082	3.0	4197	0.1754	0.9612	0.9612

Framework versions

• Transformers 4.50.0
• Pytorch 2.6.0+cu124
• Tokenizers 0.21.1