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---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: results
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train[80%:]
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.0625
---
<!-- 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. -->
# results
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 4.5590
- Accuracy: 0.0625
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6612 | 1.0 | 40 | 3.9513 | 0.0 |
| 0.8129 | 2.0 | 80 | 3.9721 | 0.025 |
| 0.3799 | 3.0 | 120 | 4.3376 | 0.0125 |
| 0.0946 | 4.0 | 160 | 4.4142 | 0.0563 |
| 0.019 | 5.0 | 200 | 4.5590 | 0.0625 |
| 0.0062 | 6.0 | 240 | 4.9286 | 0.0437 |
| 0.0039 | 7.0 | 280 | 5.0577 | 0.0437 |
| 0.0028 | 8.0 | 320 | 5.1624 | 0.0437 |
| 0.0024 | 9.0 | 360 | 5.2316 | 0.0437 |
| 0.0023 | 10.0 | 400 | 5.2923 | 0.0437 |
| 0.0019 | 11.0 | 440 | 5.3317 | 0.0375 |
| 0.0017 | 12.0 | 480 | 5.3658 | 0.0375 |
| 0.0016 | 13.0 | 520 | 5.3915 | 0.0375 |
| 0.0016 | 14.0 | 560 | 5.4004 | 0.0375 |
| 0.0016 | 15.0 | 600 | 5.4022 | 0.0375 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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