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aadhya1803/
Aadhya-rvlcdip-vit-classifier-3

Name: Aadhya-rvlcdip-vit-classifier-3
Availability: InStock

generated_from_trainer

google/vit-base-patch16-224-in21k

finetune

apache-2.0

endpoints_compatible

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Aadhya-rvlcdip-vit-classifier-3

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.1411
Accuracy: 0.6887
Precision: 0.6883
Recall: 0.6887
F1: 0.6836

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	188	1.7333	0.549	0.6379	0.549	0.5230
No log	2.0	376	1.4089	0.636	0.6717	0.636	0.6226
1.6083	3.0	564	1.2312	0.666	0.6863	0.666	0.6715
1.6083	4.0	752	1.1426	0.7	0.7150	0.7	0.7021
1.6083	5.0	940	1.0885	0.709	0.7103	0.709	0.7072
0.6576	6.0	1128	1.0865	0.699	0.7108	0.699	0.7010
0.6576	7.0	1316	1.0942	0.69	0.7158	0.69	0.6980
0.246	8.0	1504	1.0737	0.706	0.7215	0.706	0.7110

Framework versions

Transformers 4.57.1
Pytorch 2.9.1+cu128
Datasets 4.4.1
Tokenizers 0.22.1

aadhya1803/Aadhya-rvlcdip-vit-classifier-3

Aadhya-rvlcdip-vit-classifier-3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

aadhya1803/
Aadhya-rvlcdip-vit-classifier-3