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

Loss: 0.7891
Accuracy: 0.7575

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine_with_restarts
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7123	1.0	25	0.8681	0.735
0.6349	2.0	50	0.8721	0.73
0.6354	3.0	75	0.8732	0.725
0.6189	4.0	100	0.8406	0.735
0.6364	5.0	125	0.8456	0.74
0.5833	6.0	150	0.8503	0.725
0.5384	7.0	175	0.8023	0.755
0.5297	8.0	200	0.8002	0.7525
0.5487	9.0	225	0.8253	0.745
0.5068	10.0	250	0.7891	0.7575

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1

mhdiqbalpradipta/emotion_classification

emotion_classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mhdiqbalpradipta/
emotion_classification