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resnet-18-finetuned-resnet – AI Model by embunna | AlphaNeural AI
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embunna
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resnet-18-finetuned-resnet
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transformers
tensorboard
safetensors
resnet
image-classification
generated_from_trainer
imagefolder
microsoft/resnet-18
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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resnet-18-finetuned-resnet
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: nan
Accuracy: 0.3958
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
0.8889
6
nan
0.3958
0.0
1.9259
13
nan
0.3958
0.0
2.6667
18
nan
0.3958
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1
