counterbench-roberta-base

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

• Loss: 0.4148
• Accuracy: 0.8424
• Macro F1: 0.8384

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: 32
• 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
• lr_scheduler_warmup_steps: 100
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
No log	1.0	62	0.6750	0.5576	0.3580
No log	2.0	124	0.5457	0.7515	0.7229
No log	3.0	186	0.4109	0.8061	0.8029
No log	4.0	248	0.4213	0.8121	0.8027
No log	5.0	310	0.4148	0.8424	0.8384

Framework versions

• Transformers 5.17.0
• Pytorch 2.14.0+cu130
• Datasets 3.6.0
• Tokenizers 0.23.2