modernbert-output – AI Model by davanstrien | AlphaNeural AI

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davanstrien/
modernbert-output

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text-classification

generated_from_trainer

answerdotai/ModernBERT-base

endpoints_compatible

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modernbert-output

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: 0.6180
Accuracy: 0.8867
Macro F1: 0.8872

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
3.0392	1.0	140	0.6617	0.8267	0.8251
1.4070	2.0	280	0.5377	0.8733	0.8759
0.5328	3.0	420	0.6954	0.86	0.8646
0.3036	4.0	560	0.6180	0.8867	0.8872
0.0971	5.0	700	0.6528	0.88	0.8813

Framework versions

Transformers 5.3.0
Pytorch 2.11.0+cu130
Datasets 4.8.4
Tokenizers 0.22.2