resnet-101-finetuned_resnet101-sgd-optimizer20-autotags – AI Model by priyankloco | AlphaNeural AI

You can deploy this model and start earning money today!

priyankloco/
resnet-101-finetuned_resnet101-sgd-optimizer20-autotags

like

0

image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

resnet-101-finetuned_resnet101-sgd-optimizer20-autotags

This model is a fine-tuned version of microsoft/resnet-101 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.3318
Accuracy: 0.8848

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: 0.1
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
1.1302	0.99	65	1.0040	0.6724
1.1708	1.99	130	1.4856	0.5495
1.141	2.99	195	1.1486	0.6352
1.0119	3.99	260	0.8829	0.7314
0.8091	4.99	325	0.8301	0.7419
0.7878	5.99	390	0.8121	0.7333
0.6827	6.99	455	0.6047	0.7990
0.5525	7.99	520	0.6028	0.8048
0.5787	8.99	585	0.5183	0.8352
0.4797	9.99	650	0.4737	0.8543
0.4224	10.99	715	0.4943	0.8305
0.4389	11.99	780	0.4162	0.8629
0.4142	12.99	845	0.4000	0.8629
0.3144	13.99	910	0.3833	0.8695
0.2915	14.99	975	0.3688	0.8733
0.3302	15.99	1040	0.3643	0.8810
0.2954	16.99	1105	0.3446	0.8867
0.2186	17.99	1170	0.3571	0.8905
0.1812	18.99	1235	0.3334	0.8886
0.1911	19.99	1300	0.3318	0.8848

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.11.0
Tokenizers 0.13.2