metadata

license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: convnextv2-base-22k-384-finetuned-cassava-leaf-disease
    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: 0.8785046728971962

convnextv2-base-22k-384-finetuned-cassava-leaf-disease

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

Loss: 0.3755
Accuracy: 0.8785

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: 140
eval_batch_size: 140
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 560
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
0.7713	0.99	34	0.5754	0.7949
0.3953	2.0	69	0.3769	0.8650
0.3478	2.99	103	0.3717	0.8673
0.3296	4.0	138	0.3696	0.8752
0.3058	4.99	172	0.3387	0.8808
0.2791	6.0	207	0.3480	0.8804
0.2541	6.99	241	0.3483	0.8799
0.247	8.0	276	0.3590	0.8743
0.2395	8.99	310	0.3505	0.8794
0.2139	10.0	345	0.3702	0.8766
0.2116	10.99	379	0.3702	0.8766
0.204	12.0	414	0.3661	0.8762
0.183	12.99	448	0.3705	0.8776
0.1856	14.0	483	0.3861	0.8780
0.1641	14.99	517	0.3758	0.8766
0.1784	15.77	544	0.3755	0.8785

Framework versions

Transformers 4.39.3
Pytorch 2.2.1
Datasets 2.18.0
Tokenizers 0.15.1