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resnet-50-finetuned-eurosat – AI Model by sngsfydy | AlphaNeural AI
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resnet-50-finetuned-eurosat
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transformers
pytorch
tensorboard
resnet
image-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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resnet-50-finetuned-eurosat
This model is a fine-tuned version of
microsoft/resnet-50
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.0706
Accuracy: 0.5152
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: 20
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.6069
0.99
20
1.5839
0.3879
1.5395
1.98
40
1.4860
0.5485
1.4321
2.96
60
1.3500
0.5364
1.3292
4.0
81
1.1826
0.5212
1.233
4.99
101
1.0706
0.5152
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.0
Tokenizers 0.13.3
