|
--- |
|
license: apache-2.0 |
|
base_model: facebook/convnextv2-base-1k-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: Expert1-leaf-disease-convnextv2-base-1k-224-0_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: 0.776566757493188 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Expert1-leaf-disease-convnextv2-base-1k-224-0_4 |
|
|
|
This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5130 |
|
- Accuracy: 0.7766 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 0.73 | 2 | 1.5191 | 0.4986 | |
|
| No log | 1.82 | 5 | 1.1824 | 0.7003 | |
|
| No log | 2.91 | 8 | 0.9376 | 0.7030 | |
|
| 1.2488 | 4.0 | 11 | 0.7720 | 0.7030 | |
|
| 1.2488 | 4.73 | 13 | 0.7011 | 0.7057 | |
|
| 1.2488 | 5.82 | 16 | 0.6272 | 0.7275 | |
|
| 1.2488 | 6.91 | 19 | 0.5783 | 0.7738 | |
|
| 0.6707 | 8.0 | 22 | 0.5519 | 0.7820 | |
|
| 0.6707 | 8.73 | 24 | 0.5381 | 0.7711 | |
|
| 0.6707 | 9.82 | 27 | 0.5263 | 0.7684 | |
|
| 0.5104 | 10.91 | 30 | 0.5152 | 0.7738 | |
|
| 0.5104 | 11.64 | 32 | 0.5130 | 0.7766 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.3 |
|
- Pytorch 2.2.1 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.1 |
|
|
