This model is a fine-tuned version of barghavani/Cheese_xray on the chest-xray-classification dataset. It achieves the following results on the evaluation set:

Loss: 0.2827
Accuracy: 0.8883

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3993	0.99	63	0.4364	0.7165
0.3454	1.99	127	0.3947	0.7680
0.3327	3.0	191	0.3582	0.8591
0.3329	4.0	255	0.3371	0.8746
0.2992	4.99	318	0.3449	0.8643
0.3289	5.99	382	0.3172	0.8832
0.3309	7.0	446	0.2956	0.8935
0.2875	8.0	510	0.2911	0.8883
0.2764	8.99	573	0.2884	0.9124
0.265	9.88	630	0.2827	0.8883

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0