---
base_model: microsoft/beit-large-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Train-Augmentation-beit-large
  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. -->

# Train-Augmentation-beit-large

This model is a fine-tuned version of [microsoft/beit-large-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-large-patch16-224-pt22k-ft22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8592
- Accuracy: 0.8182

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0993        | 0.99  | 93   | 0.6675          | 0.8340   |
| 0.0492        | 2.0   | 187  | 0.8597          | 0.8379   |
| 0.0134        | 2.99  | 280  | 0.7961          | 0.8024   |
| 0.0016        | 4.0   | 374  | 0.7594          | 0.8340   |
| 0.0004        | 4.97  | 465  | 0.8592          | 0.8182   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2