resnet-50-finetuned-eurosat – AI Model by Aditi3004 | AlphaNeural AI

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Aditi3004/
resnet-50-finetuned-eurosat

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image-classification

generated_from_trainer

microsoft/resnet-50

autotrain_compatible

endpoints_compatible

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resnet-50-finetuned-eurosat

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

Loss: 0.6309
Accuracy: 0.5625

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	3	0.6749	0.5625
No log	2.0	6	0.6746	0.5625
No log	3.0	9	0.6696	0.5625
2.1049	4.0	12	0.6614	0.5312
2.1049	5.0	15	0.6552	0.5625
2.1049	6.0	18	0.6494	0.5625
2.0436	7.0	21	0.6427	0.5625
2.0436	8.0	24	0.6399	0.5625
2.0436	9.0	27	0.6325	0.5625
1.7828	10.0	30	0.6314	0.5625
1.7828	11.0	33	0.6309	0.5625

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0