|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- image_folder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: vit-base-patch16-224-in21k-finetuned-cassava |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: image_folder |
|
type: image_folder |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8761682242990654 |
|
--- |
|
|
|
<!-- 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-in21k-finetuned-cassava |
|
|
|
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the image_folder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3875 |
|
- Accuracy: 0.8762 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- 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: 0.1 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.5531 | 1.0 | 535 | 0.4938 | 0.8336 | |
|
| 0.4139 | 2.0 | 1070 | 0.4071 | 0.8612 | |
|
| 0.287 | 3.0 | 1605 | 0.3954 | 0.8643 | |
|
| 0.4211 | 4.0 | 2140 | 0.3906 | 0.8701 | |
|
| 0.316 | 5.0 | 2675 | 0.3716 | 0.8755 | |
|
| 0.2709 | 6.0 | 3210 | 0.3784 | 0.8736 | |
|
| 0.177 | 7.0 | 3745 | 0.3772 | 0.8745 | |
|
| 0.2409 | 8.0 | 4280 | 0.3875 | 0.8762 | |
|
| 0.1929 | 9.0 | 4815 | 0.3915 | 0.8708 | |
|
| 0.1877 | 10.0 | 5350 | 0.3881 | 0.8715 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.20.1 |
|
- Pytorch 1.11.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|
