---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: classifier-posterior-glare-removal
  results: []
---

<!-- 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. -->

# classifier-posterior-glare-removal

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 classifier_posterior_glare_removal_256_crop_s1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4990
- Accuracy: 0.8593

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.626         | 0.8065 | 50   | 0.5622          | 0.7582   |
| 0.4848        | 1.6129 | 100  | 0.5952          | 0.6675   |
| 0.2195        | 2.4194 | 150  | 0.5258          | 0.8325   |
| 0.1967        | 3.2258 | 200  | 0.5911          | 0.7960   |
| 0.2945        | 4.0323 | 250  | 0.4966          | 0.8300   |
| 0.1866        | 4.8387 | 300  | 0.5222          | 0.8350   |
| 0.1211        | 5.6452 | 350  | 0.5328          | 0.8426   |
| 0.1666        | 6.4516 | 400  | 0.5545          | 0.8426   |
| 0.0737        | 7.2581 | 450  | 0.5327          | 0.8526   |
| 0.0314        | 8.0645 | 500  | 0.5208          | 0.8526   |
| 0.0329        | 8.8710 | 550  | 0.5773          | 0.8489   |
| 0.0497        | 9.6774 | 600  | 0.5994          | 0.8489   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1