This model is a fine-tuned version of microsoft/deberta-v3-large on the PAN CLEF 2025 dataset. It achieves the following results on the evaluation set:

Loss: 0.1185
Accuracy: 0.9728
Precision: 0.9735
Recall: 0.9728
F1: 0.9729

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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.3364	1.0	556	0.1755	0.9550	0.9572	0.9550	0.9552
0.2607	2.0	1112	0.2262	0.9347	0.9379	0.9347	0.9337
0.1895	3.0	1668	0.1562	0.9592	0.9619	0.9592	0.9595
0.1558	4.0	2224	0.1673	0.9627	0.9632	0.9627	0.9625
0.1617	5.0	2780	0.1505	0.9657	0.9659	0.9657	0.9658
0.1394	6.0	3336	0.1359	0.9632	0.9657	0.9632	0.9635
0.1354	7.0	3892	0.1310	0.9725	0.9725	0.9725	0.9725
0.1192	8.0	4448	0.1238	0.9683	0.9699	0.9683	0.9685
0.1096	9.0	5004	0.1222	0.9742	0.9744	0.9742	0.9742
0.1127	10.0	5560	0.1185	0.9728	0.9735	0.9728	0.9729

Framework versions

Transformers 4.45.2
Pytorch 2.4.1
Datasets 3.0.0
Tokenizers 0.20.1

Shushant/panclef_data_deberta_finetuned

panclef_data_deberta_finetuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Shushant/
panclef_data_deberta_finetuned