This model is a fine-tuned version of Celal11/resnet-50-finetuned-FER2013-0.003 on the image_folder dataset. It achieves the following results on the evaluation set:

Loss: 0.0614
Accuracy: 0.9848

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: 0.003
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6689	0.97	27	0.1123	0.9797
0.2929	1.97	54	0.0614	0.9848

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1

Celal11/resnet-50-finetuned-FER2013-0.003-CKPlus

resnet-50-finetuned-FER2013-0.003-CKPlus

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Celal11/
resnet-50-finetuned-FER2013-0.003-CKPlus