metadata

license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: BaseModel-leaf-disease-convnextv2-base-22k-224-0_1_2_3_4
    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: 0.8813084112149533

BaseModel-leaf-disease-convnextv2-base-22k-224-0_1_2_3_4

This model is a fine-tuned version of facebook/convnextv2-base-22k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.3419
Accuracy: 0.8813

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: 300
eval_batch_size: 300
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 1200
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4178	0.98	16	0.9457	0.6215
0.6112	1.97	32	0.4856	0.8294
0.4468	2.95	48	0.4163	0.8575
0.3659	4.0	65	0.3790	0.8715
0.3481	4.98	81	0.3655	0.8785
0.3338	5.97	97	0.3637	0.8748
0.3216	6.95	113	0.3568	0.8752
0.2948	8.0	130	0.3493	0.8808
0.2944	8.98	146	0.3483	0.8808
0.2857	9.97	162	0.3474	0.8808
0.2711	10.95	178	0.3442	0.8790
0.2682	12.0	195	0.3418	0.8813
0.252	12.98	211	0.3409	0.8827
0.2598	13.97	227	0.3405	0.8827
0.2621	14.95	243	0.3432	0.8813
0.2602	15.75	256	0.3419	0.8813

Framework versions

Transformers 4.39.3
Pytorch 2.2.1
Datasets 2.18.0
Tokenizers 0.15.1