resnet-18-finetuned – AI Model by embunna | AlphaNeural AI

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embunna/
resnet-18-finetuned

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image-classification

generated_from_trainer

microsoft/resnet-18

autotrain_compatible

endpoints_compatible

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resnet-18-finetuned

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: 48006217018842836977297404198912.0000
Accuracy: 0.3646

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	48006217018842836977297404198912.0000	0.3646
50170425382569737119999364956160.0000	1.9259	13	48006217018842836977297404198912.0000	0.3646
50170425382569737119999364956160.0000	2.6667	18	48006217018842836977297404198912.0000	0.3646

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1