cvt-13-finetuned-IDRiD – AI Model by SJChaudhuri | AlphaNeural AI

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SJChaudhuri/
cvt-13-finetuned-IDRiD

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image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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cvt-13-finetuned-IDRiD

This model is a fine-tuned version of microsoft/cvt-13 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2520
Accuracy: 0.4524

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
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
No log	1.0	3	1.6800	0.1190
No log	2.0	6	1.6686	0.2143
No log	3.0	9	1.5528	0.3333
1.6061	4.0	12	1.4874	0.3333
1.6061	5.0	15	1.4834	0.3571
1.6061	6.0	18	1.4485	0.3810
1.4325	7.0	21	1.4295	0.4048
1.4325	8.0	24	1.4172	0.4286
1.4325	9.0	27	1.3890	0.4048
1.3474	10.0	30	1.3739	0.4286
1.3474	11.0	33	1.3571	0.4048
1.3474	12.0	36	1.3244	0.4048
1.3474	13.0	39	1.3090	0.4048
1.3039	14.0	42	1.3438	0.4286
1.3039	15.0	45	1.3617	0.4286
1.3039	16.0	48	1.3513	0.4286
1.2892	17.0	51	1.3187	0.4524
1.2892	18.0	54	1.3054	0.3810
1.2892	19.0	57	1.2862	0.4286
1.2489	20.0	60	1.2670	0.4524
1.2489	21.0	63	1.2810	0.4762
1.2489	22.0	66	1.2389	0.4524
1.2489	23.0	69	1.2312	0.4762
1.2378	24.0	72	1.2619	0.4524
1.2378	25.0	75	1.2652	0.4524
1.2378	26.0	78	1.2639	0.4524
1.1968	27.0	81	1.2517	0.4524
1.1968	28.0	84	1.2603	0.4286
1.1968	29.0	87	1.2463	0.4524
1.1977	30.0	90	1.2520	0.4524

Framework versions

Transformers 4.30.0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.13.3