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resnet-50-finetuned-FBark – AI Model by alyzbane | AlphaNeural AI
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resnet-50-finetuned-FBark
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transformers
safetensors
resnet
image-classification
generated_from_trainer
imagefolder
microsoft/resnet-50
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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resnet-50-finetuned-FBark
This model is a fine-tuned version of
microsoft/resnet-50
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.1079
Precision: 0.9699
Recall: 0.9779
F1: 0.9735
Accuracy: 0.9720
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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 35
Training results
Framework versions
Transformers 4.39.3
Pytorch 2.2.0+cpu
Datasets 2.19.0
Tokenizers 0.15.1
