---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Birdsclassification
  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. -->

# Birdsclassification

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3057
- Accuracy: 0.9307

## 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: 0.0003
- 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: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.42          | 1.0   | 262  | 3.6698          | 0.7571   |
| 1.7968        | 2.0   | 525  | 0.9179          | 0.8396   |
| 0.6598        | 3.0   | 787  | 0.6370          | 0.8654   |
| 0.4867        | 4.0   | 1050 | 0.5493          | 0.8765   |
| 0.4055        | 5.0   | 1312 | 0.5093          | 0.8833   |
| 0.3513        | 6.0   | 1575 | 0.4602          | 0.8892   |
| 0.3053        | 7.0   | 1837 | 0.4350          | 0.8977   |
| 0.2692        | 8.0   | 2100 | 0.4130          | 0.9021   |
| 0.2446        | 9.0   | 2362 | 0.4218          | 0.9018   |
| 0.2267        | 10.0  | 2625 | 0.3667          | 0.9130   |
| 0.2018        | 11.0  | 2887 | 0.3632          | 0.9154   |
| 0.1842        | 12.0  | 3150 | 0.3533          | 0.9154   |
| 0.1636        | 13.0  | 3412 | 0.3396          | 0.9206   |
| 0.1511        | 14.0  | 3675 | 0.3125          | 0.9266   |
| 0.1411        | 15.0  | 3937 | 0.2833          | 0.9329   |
| 0.1259        | 15.97 | 4192 | 0.3057          | 0.9307   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2