metadata

license: apache-2.0
base_model: facebook/convnextv2-nano-22k-384
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: convnext-nano-20ep
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: vuongnhathien/30VNFoods
          type: imagefolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8702380952380953

convnext-nano-20ep

This model is a fine-tuned version of facebook/convnextv2-nano-22k-384 on the vuongnhathien/30VNFoods dataset. It achieves the following results on the evaluation set:

Loss: 0.4812
Accuracy: 0.8702

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: 0.0003
train_batch_size: 64
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5831	1.0	275	0.5660	0.8278
0.3159	2.0	550	0.5093	0.8529
0.1892	3.0	825	0.4719	0.8779
0.1111	4.0	1100	0.5067	0.8755
0.0886	5.0	1375	0.5278	0.8708
0.0697	6.0	1650	0.6000	0.8628
0.0396	7.0	1925	0.6158	0.8736
0.0386	8.0	2200	0.6448	0.8684
0.0323	9.0	2475	0.5637	0.8915
0.0157	10.0	2750	0.5845	0.8958
0.0067	11.0	3025	0.5574	0.9018
0.005	12.0	3300	0.5378	0.9034
0.0031	13.0	3575	0.5526	0.9014
0.0023	14.0	3850	0.5419	0.9093
0.0026	15.0	4125	0.5323	0.9113
0.0024	16.0	4400	0.5298	0.9117
0.0019	17.0	4675	0.5323	0.9121
0.002	18.0	4950	0.5315	0.9125
0.0012	19.0	5225	0.5314	0.9121
0.0019	20.0	5500	0.5315	0.9117

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2