metadata

license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: finetuned-Leukemia-cell
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9624060150375939

finetuned-Leukemia-cell

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0946
Accuracy: 0.9624

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: 0.0002
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9733	2.94	100	0.8894	0.7256
0.7184	5.88	200	0.7876	0.7293
0.5299	8.82	300	0.5183	0.8609
0.3991	11.76	400	0.3121	0.8947
0.2263	14.71	500	0.1337	0.9549
0.1782	17.65	600	0.0946	0.9624

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0