---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: beit-base-patch16-224
  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. -->

# beit-base-patch16-224

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co./microsoft/beit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3575
- Accuracy: 0.9456
- Precision: 0.9498
- Recall: 0.9456
- F1 Score: 0.9473

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 45

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| No log        | 0.94  | 4    | 0.3212          | 0.8475   | 0.8711    | 0.8475 | 0.7915   |
| No log        | 1.88  | 8    | 0.2355          | 0.8983   | 0.8925    | 0.8983 | 0.8937   |
| No log        | 2.82  | 12   | 0.3134          | 0.8644   | 0.8834    | 0.8644 | 0.8243   |
| 0.2493        | 4.0   | 17   | 0.2434          | 0.8814   | 0.8962    | 0.8814 | 0.8534   |
| 0.2493        | 4.94  | 21   | 0.3406          | 0.8983   | 0.9094    | 0.8983 | 0.8794   |
| 0.2493        | 5.88  | 25   | 0.1131          | 0.9322   | 0.9300    | 0.9322 | 0.9291   |
| 0.2493        | 6.82  | 29   | 0.1727          | 0.9153   | 0.9435    | 0.9153 | 0.9215   |
| 0.0374        | 8.0   | 34   | 0.6181          | 0.8644   | 0.8834    | 0.8644 | 0.8243   |
| 0.0374        | 8.94  | 38   | 0.3249          | 0.9153   | 0.9125    | 0.9153 | 0.9135   |
| 0.0374        | 9.88  | 42   | 0.5308          | 0.8983   | 0.8934    | 0.8983 | 0.8876   |
| 0.007         | 10.82 | 46   | 0.4767          | 0.9153   | 0.9119    | 0.9153 | 0.9090   |
| 0.007         | 12.0  | 51   | 0.3883          | 0.8983   | 0.8925    | 0.8983 | 0.8937   |
| 0.007         | 12.94 | 55   | 0.3627          | 0.8983   | 0.8934    | 0.8983 | 0.8876   |
| 0.007         | 13.88 | 59   | 0.2783          | 0.9492   | 0.9479    | 0.9492 | 0.9481   |
| 0.0012        | 14.82 | 63   | 0.1934          | 0.9492   | 0.9519    | 0.9492 | 0.9501   |
| 0.0012        | 16.0  | 68   | 0.1670          | 0.9661   | 0.9661    | 0.9661 | 0.9661   |
| 0.0012        | 16.94 | 72   | 0.1783          | 0.9492   | 0.9479    | 0.9492 | 0.9481   |
| 0.0001        | 17.88 | 76   | 0.4825          | 0.9322   | 0.9373    | 0.9322 | 0.9251   |
| 0.0001        | 18.82 | 80   | 0.9010          | 0.8983   | 0.9094    | 0.8983 | 0.8794   |
| 0.0001        | 20.0  | 85   | 0.1802          | 0.9661   | 0.9718    | 0.9661 | 0.9673   |
| 0.0001        | 20.94 | 89   | 0.5658          | 0.9153   | 0.9119    | 0.9153 | 0.9090   |
| 0.0037        | 21.88 | 93   | 0.8331          | 0.9322   | 0.9373    | 0.9322 | 0.9251   |
| 0.0037        | 22.82 | 97   | 0.8074          | 0.9153   | 0.9119    | 0.9153 | 0.9090   |
| 0.0037        | 24.0  | 102  | 0.4763          | 0.8814   | 0.8771    | 0.8814 | 0.8788   |
| 0.0002        | 24.94 | 106  | 0.5553          | 0.9153   | 0.9119    | 0.9153 | 0.9090   |
| 0.0002        | 25.88 | 110  | 0.8220          | 0.9153   | 0.9231    | 0.9153 | 0.9032   |
| 0.0002        | 26.82 | 114  | 0.5367          | 0.9322   | 0.9373    | 0.9322 | 0.9251   |
| 0.0002        | 28.0  | 119  | 0.4401          | 0.9153   | 0.9298    | 0.9153 | 0.9194   |
| 0.0037        | 28.94 | 123  | 0.4138          | 0.9153   | 0.9125    | 0.9153 | 0.9135   |
| 0.0037        | 29.88 | 127  | 0.7232          | 0.8983   | 0.9094    | 0.8983 | 0.8794   |
| 0.0037        | 30.82 | 131  | 0.3690          | 0.9322   | 0.9373    | 0.9322 | 0.9251   |
| 0.0115        | 32.0  | 136  | 0.2730          | 0.9322   | 0.9400    | 0.9322 | 0.9346   |
| 0.0115        | 32.94 | 140  | 0.2101          | 0.9661   | 0.9661    | 0.9661 | 0.9661   |
| 0.0115        | 33.88 | 144  | 0.1814          | 0.9661   | 0.9661    | 0.9661 | 0.9661   |
| 0.0115        | 34.82 | 148  | 0.1641          | 0.9661   | 0.9661    | 0.9661 | 0.9661   |
| 0.0013        | 36.0  | 153  | 0.1600          | 0.9492   | 0.9479    | 0.9492 | 0.9481   |
| 0.0013        | 36.94 | 157  | 0.1709          | 0.9661   | 0.9674    | 0.9661 | 0.9646   |
| 0.0013        | 37.88 | 161  | 0.1913          | 0.9661   | 0.9674    | 0.9661 | 0.9646   |
| 0.0001        | 38.82 | 165  | 0.2047          | 0.9661   | 0.9674    | 0.9661 | 0.9646   |
| 0.0001        | 40.0  | 170  | 0.2030          | 0.9661   | 0.9674    | 0.9661 | 0.9646   |
| 0.0001        | 40.94 | 174  | 0.1960          | 0.9661   | 0.9674    | 0.9661 | 0.9646   |
| 0.0001        | 41.88 | 178  | 0.1936          | 0.9661   | 0.9674    | 0.9661 | 0.9646   |
| 0.0003        | 42.35 | 180  | 0.1934          | 0.9661   | 0.9674    | 0.9661 | 0.9646   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2