Chess_Images

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

• Loss: 0.5284
• Accuracy: 0.9

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
No log	1.0	2	1.0120	0.7
No log	2.0	4	0.9958	0.8
No log	3.0	6	0.9576	0.8333
No log	4.0	8	0.8673	0.8333
0.8292	5.0	10	0.8140	0.8667
0.8292	6.0	12	0.7034	0.9
0.8292	7.0	14	0.7036	0.9
0.8292	8.0	16	0.6949	0.9333
0.8292	9.0	18	0.5620	0.9667
0.6112	10.0	20	0.5829	0.9333
0.6112	11.0	22	0.6530	0.9
0.6112	12.0	24	0.5664	0.9333
0.6112	13.0	26	0.5084	1.0
0.6112	14.0	28	0.6490	0.8333
0.4805	15.0	30	0.4700	1.0
0.4805	16.0	32	0.5473	0.9333
0.4805	17.0	34	0.4928	0.9667
0.4805	18.0	36	0.5023	0.9667
0.4805	19.0	38	0.4885	0.9333
0.4145	20.0	40	0.5284	0.9

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2