This model is a fine-tuned version of CGCTG/orientation_resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.5106
Accuracy: 0.7598

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: 0.05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7836	1.0	87	1.2301	0.4986
0.6808	2.0	174	0.6659	0.6382
0.5641	2.9711	258	0.5106	0.7598

Framework versions

Transformers 4.48.0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0