transformers safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: out
  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. -->

# out

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3251
- Accuracy: 0.8761

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6237        | 0.99  | 43   | 0.5558          | 0.7302   |
| 0.462         | 1.99  | 86   | 0.4139          | 0.8248   |
| 0.4174        | 2.98  | 129  | 0.3704          | 0.8468   |
| 0.4089        | 4.0   | 173  | 0.4138          | 0.8231   |
| 0.3656        | 4.99  | 216  | 0.3322          | 0.8688   |
| 0.3282        | 5.99  | 259  | 0.3251          | 0.8761   |
| 0.3251        | 6.98  | 302  | 0.3296          | 0.8696   |
| 0.3025        | 8.0   | 346  | 0.3221          | 0.8720   |
| 0.2937        | 8.99  | 389  | 0.3218          | 0.8729   |
| 0.2812        | 9.94  | 430  | 0.3219          | 0.8753   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
