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resnet-18-finetuned-eurosat – AI Model by satani | AlphaNeural AI
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resnet-18-finetuned-eurosat
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transformers
pytorch
resnet
image-classification
generated_from_trainer
imagefolder
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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resnet-18-finetuned-eurosat
This model is a fine-tuned version of
microsoft/resnet-18
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 3.5651
Accuracy: 0.0
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: 1
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.9039
1.0
65
3.5209
0.0
0.6023
2.0
130
3.3549
0.0
0.6882
3.0
195
3.5651
0.0
Framework versions
Transformers 4.29.2
Pytorch 1.12.1
Datasets 2.12.0
Tokenizers 0.13.3
