README.md

metadata

library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: modernbert-tr-classifier
    results: []

modernbert-tr-classifier

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

• Loss: 0.6006
• F1: 0.9060
• Accuracy: 0.9061

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: 8e-05
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
1.7403	1.0	73	1.2040	0.5117	0.5429
1.036	2.0	146	0.7293	0.7292	0.7347
0.6043	3.0	219	0.5232	0.8202	0.8163
0.3395	4.0	292	0.3972	0.8602	0.8571
0.173	5.0	365	0.4365	0.8548	0.8571
0.0784	6.0	438	0.4332	0.8667	0.8653
0.0445	7.0	511	0.5221	0.8856	0.8857
0.0354	8.0	584	0.5177	0.9023	0.9020
0.0239	9.0	657	0.8380	0.8676	0.8653
0.0199	10.0	730	0.6887	0.8755	0.8735
0.017	11.0	803	0.6245	0.9013	0.9020
0.0058	12.0	876	0.5052	0.9147	0.9143
0.0051	13.0	949	0.6583	0.8834	0.8816
0.0049	14.0	1022	0.6444	0.8889	0.8898
0.0021	15.0	1095	0.7612	0.8761	0.8776
0.001	16.0	1168	0.6017	0.9143	0.9143
0.0005	17.0	1241	0.6069	0.9016	0.9020
0.0005	18.0	1314	0.6110	0.9019	0.9020
0.0004	19.0	1387	0.6050	0.9019	0.9020
0.0004	20.0	1460	0.6006	0.9060	0.9061

Framework versions

• Transformers 4.48.0
• Pytorch 2.5.1+cu118
• Datasets 3.1.0
• Tokenizers 0.21.0