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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification
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: 0.61875
---
<!-- 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. -->
# image_classification
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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2094
- Accuracy: 0.6188
## 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: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8174 | 1.0 | 10 | 1.8349 | 0.4062 |
| 1.7364 | 2.0 | 20 | 1.6966 | 0.4 |
| 1.6087 | 3.0 | 30 | 1.5892 | 0.45 |
| 1.4904 | 4.0 | 40 | 1.4914 | 0.4875 |
| 1.4009 | 5.0 | 50 | 1.4288 | 0.5125 |
| 1.3129 | 6.0 | 60 | 1.3619 | 0.575 |
| 1.2233 | 7.0 | 70 | 1.3622 | 0.5687 |
| 1.1419 | 8.0 | 80 | 1.3047 | 0.5188 |
| 1.094 | 9.0 | 90 | 1.2763 | 0.6062 |
| 1.0366 | 10.0 | 100 | 1.2496 | 0.5625 |
| 0.9785 | 11.0 | 110 | 1.2368 | 0.6 |
| 0.9435 | 12.0 | 120 | 1.1960 | 0.6438 |
| 0.9031 | 13.0 | 130 | 1.2083 | 0.5563 |
| 0.8829 | 14.0 | 140 | 1.2629 | 0.5188 |
| 0.824 | 15.0 | 150 | 1.2061 | 0.5938 |
| 0.7952 | 16.0 | 160 | 1.2630 | 0.55 |
| 0.7744 | 17.0 | 170 | 1.2329 | 0.5625 |
| 0.7487 | 18.0 | 180 | 1.2259 | 0.5437 |
| 0.7381 | 19.0 | 190 | 1.1750 | 0.5813 |
| 0.7261 | 20.0 | 200 | 1.1802 | 0.575 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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