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---
library_name: transformers
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: 0.625
---
<!-- 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: 1.2826
- Accuracy: 0.625
## 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.071 | 1.0 | 10 | 2.0532 | 0.2125 |
| 1.9763 | 2.0 | 20 | 1.9614 | 0.3312 |
| 1.8031 | 3.0 | 30 | 1.8326 | 0.4562 |
| 1.6168 | 4.0 | 40 | 1.7015 | 0.5125 |
| 1.4508 | 5.0 | 50 | 1.6065 | 0.5188 |
| 1.3037 | 6.0 | 60 | 1.5397 | 0.5375 |
| 1.1709 | 7.0 | 70 | 1.4836 | 0.55 |
| 1.0481 | 8.0 | 80 | 1.4248 | 0.5813 |
| 0.9441 | 9.0 | 90 | 1.3915 | 0.5625 |
| 0.8551 | 10.0 | 100 | 1.3586 | 0.6 |
| 0.7772 | 11.0 | 110 | 1.3315 | 0.6 |
| 0.7174 | 12.0 | 120 | 1.3057 | 0.6062 |
| 0.6721 | 13.0 | 130 | 1.2936 | 0.6188 |
| 0.642 | 14.0 | 140 | 1.2933 | 0.6 |
| 0.6252 | 15.0 | 150 | 1.2826 | 0.625 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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