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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: 0.46875
---
<!-- 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: 1.4301
- Accuracy: 0.4688
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0867 | 1.0 | 10 | 2.0602 | 0.1938 |
| 2.0294 | 2.0 | 20 | 1.9887 | 0.2562 |
| 1.9159 | 3.0 | 30 | 1.8738 | 0.3438 |
| 1.763 | 4.0 | 40 | 1.7523 | 0.375 |
| 1.6138 | 5.0 | 50 | 1.6505 | 0.4 |
| 1.5141 | 6.0 | 60 | 1.5861 | 0.4125 |
| 1.4328 | 7.0 | 70 | 1.5303 | 0.45 |
| 1.3357 | 8.0 | 80 | 1.4986 | 0.475 |
| 1.2833 | 9.0 | 90 | 1.4628 | 0.4688 |
| 1.2248 | 10.0 | 100 | 1.4501 | 0.5 |
| 1.1796 | 11.0 | 110 | 1.3972 | 0.4875 |
| 1.1526 | 12.0 | 120 | 1.4359 | 0.4813 |
| 1.1177 | 13.0 | 130 | 1.4077 | 0.4813 |
| 1.1006 | 14.0 | 140 | 1.3942 | 0.5 |
| 1.0679 | 15.0 | 150 | 1.3934 | 0.4875 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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