|
--- |
|
license: apache-2.0 |
|
base_model: xiaopch/vit-base-patch16-224-finetuned |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: vit-base-patch16-224-finetuned-for-agricultural |
|
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: 0.7309236947791165 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# vit-base-patch16-224-finetuned-for-agricultural |
|
|
|
This model is a fine-tuned version of [xiaopch/vit-base-patch16-224-finetuned](https://huggingface.co/xiaopch/vit-base-patch16-224-finetuned) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9246 |
|
- Accuracy: 0.7309 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.9131 | 1.0 | 35 | 1.0878 | 0.6847 | |
|
| 0.8066 | 2.0 | 70 | 0.9933 | 0.7189 | |
|
| 0.7259 | 3.0 | 105 | 0.9445 | 0.7249 | |
|
| 0.6719 | 4.0 | 140 | 0.9246 | 0.7309 | |
|
| 0.6056 | 5.0 | 175 | 0.9258 | 0.7229 | |
|
| 0.5576 | 6.0 | 210 | 0.9230 | 0.7309 | |
|
| 0.5113 | 7.0 | 245 | 0.9152 | 0.7169 | |
|
| 0.488 | 8.0 | 280 | 0.9119 | 0.7209 | |
|
| 0.4822 | 9.0 | 315 | 0.9061 | 0.7269 | |
|
| 0.4163 | 10.0 | 350 | 0.9039 | 0.7289 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
