metadata

license: apache-2.0
base_model: facebook/convnext-tiny-224
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: 0.9887218045112782

finetuned-Leukemia-cell

This model is a fine-tuned version of facebook/convnext-tiny-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0732
Accuracy: 0.9887

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: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2908	2.94	100	0.1524	0.9511
0.1806	5.88	200	0.1269	0.9586
0.1135	8.82	300	0.0720	0.9774
0.1061	11.76	400	0.1519	0.9624
0.0816	14.71	500	0.1845	0.9398
0.0815	17.65	600	0.0966	0.9737
0.0741	20.59	700	0.1029	0.9812
0.0423	23.53	800	0.1519	0.9699
0.0468	26.47	900	0.0757	0.9850
0.0249	29.41	1000	0.0859	0.9850
0.0443	32.35	1100	0.0878	0.9774
0.0291	35.29	1200	0.0487	0.9887
0.0263	38.24	1300	0.0643	0.9887
0.0239	41.18	1400	0.1042	0.9774
0.0331	44.12	1500	0.0679	0.9887
0.0103	47.06	1600	0.0723	0.9887
0.0131	50.0	1700	0.0732	0.9887

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0