modernbert-clinc

This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1681
• Accuracy: 0.9690
• F1: 0.9687

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: 7e-05
• train_batch_size: 64
• 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: cosine
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
2.3344	0.6276	150	0.5836	0.8506	0.8448
0.3067	1.2552	300	0.3733	0.9139	0.9111
0.2089	1.8828	450	0.2463	0.9474	0.9470
0.1132	2.5105	600	0.2390	0.9487	0.9486
0.0618	3.1381	750	0.2183	0.9587	0.9582
0.0456	3.7657	900	0.1987	0.9616	0.9611
0.0377	4.3933	1050	0.1871	0.9655	0.9650
0.0204	5.0209	1200	0.1688	0.9684	0.9681
0.0092	5.6485	1350	0.1681	0.9690	0.9687

Framework versions

• Transformers 4.52.4
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.2