---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_beit_base_f1
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8888888888888888
---

<!-- 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. -->

# hushem_40x_beit_base_f1

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9231
- Accuracy: 0.8889

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0764        | 1.0   | 107  | 0.7220          | 0.8      |
| 0.0168        | 2.0   | 214  | 1.0516          | 0.8      |
| 0.0193        | 2.99  | 321  | 1.1697          | 0.7556   |
| 0.0111        | 4.0   | 429  | 0.9218          | 0.8222   |
| 0.0033        | 5.0   | 536  | 1.0001          | 0.8444   |
| 0.0048        | 6.0   | 643  | 1.0798          | 0.8222   |
| 0.0           | 6.99  | 750  | 0.9561          | 0.8667   |
| 0.0           | 8.0   | 858  | 0.9979          | 0.8444   |
| 0.0           | 9.0   | 965  | 0.9770          | 0.8667   |
| 0.0           | 9.98  | 1070 | 0.9231          | 0.8889   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1