metadata

license: apache-2.0
base_model: facebook/convnextv2-base-1k-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Expert2-leaf-disease-convnextv2-base-1k-224-1_2_3
    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: 0.9390862944162437

Expert2-leaf-disease-convnextv2-base-1k-224-1_2_3

This model is a fine-tuned version of facebook/convnextv2-base-1k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.1892
Accuracy: 0.9391

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
1.5107	0.96	13	1.0756	0.7422
1.0022	2.0	27	0.5781	0.7603
0.4503	2.96	40	0.3902	0.8697
0.3704	4.0	54	0.3101	0.9058
0.2996	4.96	67	0.2573	0.9165
0.2405	6.0	81	0.2647	0.9075
0.2268	6.96	94	0.2259	0.9233
0.2036	8.0	108	0.2126	0.9329
0.1957	8.96	121	0.2149	0.9329
0.1885	10.0	135	0.1974	0.9385
0.1866	10.96	148	0.1983	0.9318
0.1771	12.0	162	0.2066	0.9363
0.1752	12.96	175	0.1975	0.9357
0.1744	14.0	189	0.1893	0.9380
0.1636	14.96	202	0.1889	0.9391
0.1636	15.41	208	0.1892	0.9391

Framework versions

Transformers 4.39.3
Pytorch 2.2.1
Datasets 2.18.0
Tokenizers 0.15.1