This model is a fine-tuned version of gerbejon/webpage_labeling_classifier on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.1555
Accuracy: 0.9416

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2002	0.9968	78	0.1917	0.9281
0.2191	1.9936	156	0.2132	0.9097
0.2067	2.9904	234	0.2522	0.9065
0.1751	4.0	313	0.1931	0.9217
0.1346	4.9968	391	0.1933	0.9241
0.1448	5.9936	469	0.1816	0.9313
0.1389	6.9904	547	0.2027	0.9209
0.1387	8.0	626	0.1696	0.9384
0.1234	8.9968	704	0.1758	0.9345
0.1196	9.9936	782	0.1848	0.9305
0.1213	10.9904	860	0.1769	0.9400
0.1287	12.0	939	0.1421	0.9488
0.117	12.9968	1017	0.2046	0.9241
0.1433	13.9936	1095	0.1769	0.9369
0.0988	14.9904	1173	0.1494	0.9496
0.1136	16.0	1252	0.1571	0.9424
0.086	16.9968	1330	0.1712	0.9384
0.089	17.9936	1408	0.1437	0.9440
0.0991	18.9904	1486	0.1510	0.9448
0.0824	19.9361	1560	0.1555	0.9416

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1