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cat-vs-dog-resnet-50 – AI Model by Dricz | AlphaNeural AI
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Dricz
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cat-vs-dog-resnet-50
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transformers
tensorboard
safetensors
resnet
image-classification
generated_from_trainer
cats_vs_dogs
microsoft/resnet-50
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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cat-vs-dog
This model is a fine-tuned version of
microsoft/resnet-50
on the cats_vs_dogs dataset. It achieves the following results on the evaluation set:
Loss: 0.1015
Accuracy: 0.9654
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1574
1.0
1171
0.1065
0.9624
Framework versions
Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2
