378A1_results_384_4cate_1

This model is a fine-tuned version of google/vit-base-patch16-384 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.4707
• Accuracy: 0.8997

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: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8756	1.0	37	0.5714	0.7908
0.4508	2.0	74	0.3688	0.8418
0.2344	3.0	111	0.3064	0.8741
0.1445	4.0	148	0.2948	0.8946
0.0774	5.0	185	0.3461	0.8793
0.0393	6.0	222	0.3229	0.8997
0.0164	7.0	259	0.3441	0.9048
0.0222	8.0	296	0.4192	0.9099
0.0125	9.0	333	0.4443	0.8810
0.0029	10.0	370	0.4007	0.9116
0.0014	11.0	407	0.4277	0.9150
0.0003	12.0	444	0.4445	0.9014
0.0002	13.0	481	0.4437	0.9031
0.0002	14.0	518	0.4481	0.9048
0.0002	15.0	555	0.4512	0.9031
0.0002	16.0	592	0.4537	0.9014
0.0002	17.0	629	0.4562	0.9014
0.0002	18.0	666	0.4583	0.9014
0.0001	19.0	703	0.4594	0.9014
0.0001	20.0	740	0.4615	0.9031
0.0001	21.0	777	0.4635	0.9031
0.0001	22.0	814	0.4652	0.9031
0.0001	23.0	851	0.4659	0.9031
0.0001	24.0	888	0.4679	0.8997
0.0001	25.0	925	0.4681	0.9014
0.0001	26.0	962	0.4688	0.8997
0.0001	27.0	999	0.4695	0.8997
0.0001	28.0	1036	0.4701	0.8997
0.0001	29.0	1073	0.4706	0.8997
0.0001	30.0	1110	0.4707	0.8997

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.4
• Tokenizers 0.13.3