results

This model is a fine-tuned version of cross-encoder/nli-distilroberta-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3594
• Accuracy: 0.875

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	3	0.4768	0.75
No log	2.0	6	0.4117	0.75
No log	3.0	9	0.3734	0.875
No log	4.0	12	0.3594	0.875

Framework versions

• Transformers 4.55.2
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.21.4