2025-01-21-14-35-49-resnet-50 – AI Model by alyzbane | AlphaNeural AI

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alyzbane/
2025-01-21-14-35-49-resnet-50

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image-classification

generated_from_trainer

microsoft/resnet-50

autotrain_compatible

endpoints_compatible

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2025-01-21-14-35-49-resnet-50

This model is a fine-tuned version of microsoft/resnet-50 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1215
Precision: 0.9786
Recall: 0.9778
F1: 0.9778
Accuracy: 0.9788
Top1 Accuracy: 0.9778
Error Rate: 0.0212

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: 0.0002
train_batch_size: 32
eval_batch_size: 32
seed: 3407
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	Top1 Accuracy	Error Rate
1.5858	1.0	34	1.5129	0.6583	0.5407	0.5138	0.5418	0.5407	0.4582
1.3909	2.0	68	1.1807	0.7779	0.6519	0.6537	0.6522	0.6519	0.3478
1.059	3.0	102	0.7503	0.8897	0.8889	0.8867	0.8901	0.8889	0.1099
0.6942	4.0	136	0.4029	0.9427	0.9407	0.9402	0.9427	0.9407	0.0573
0.4241	5.0	170	0.2325	0.9673	0.9630	0.9624	0.9655	0.9630	0.0345
0.3235	6.0	204	0.1702	0.9673	0.9630	0.9630	0.9650	0.9630	0.0350
0.259	7.0	238	0.1359	0.9722	0.9704	0.9704	0.9719	0.9704	0.0281
0.2231	8.0	272	0.1225	0.9722	0.9704	0.9704	0.9719	0.9704	0.0281
0.2167	9.0	306	0.1253	0.9722	0.9704	0.9704	0.9719	0.9704	0.0281
0.1973	10.0	340	0.1215	0.9786	0.9778	0.9778	0.9788	0.9778	0.0212

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.20.3