metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: >-
convnextv2-large-1k-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: Augmented-Final
split: train
args: Augmented-Final
metrics:
- name: Accuracy
type: accuracy
value: 0.986639260020555
convnextv2-large-1k-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20
This model is a fine-tuned version of facebook/convnextv2-large-1k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0976
- Accuracy: 0.9866
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8977 | 1.0 | 122 | 1.8949 | 0.2939 |
| 1.6493 | 2.0 | 244 | 1.6449 | 0.5447 |
| 1.239 | 3.0 | 366 | 1.2819 | 0.6886 |
| 0.9342 | 4.0 | 488 | 0.9664 | 0.7276 |
| 0.7011 | 5.0 | 610 | 0.6760 | 0.8356 |
| 0.5809 | 6.0 | 732 | 0.5792 | 0.8469 |
| 0.4846 | 7.0 | 854 | 0.4280 | 0.8890 |
| 0.6914 | 8.0 | 976 | 0.4121 | 0.8849 |
| 0.3815 | 9.0 | 1098 | 0.2751 | 0.9353 |
| 0.2931 | 10.0 | 1220 | 0.2980 | 0.9198 |
| 0.2485 | 11.0 | 1342 | 0.3090 | 0.9106 |
| 0.1759 | 12.0 | 1464 | 0.0976 | 0.9866 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3