transformers tensorboard safetensors beit image-classification generated_from_trainer base_model:microsoft/beit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-dmae-va-U-40
  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-dmae-va-U-40

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: 0.0573
- Accuracy: 0.9817

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 1.3991          | 0.3486   |
| 1.4669        | 1.94  | 15   | 1.2475          | 0.4128   |
| 1.1455        | 2.97  | 23   | 0.8962          | 0.5872   |
| 0.8447        | 4.0   | 31   | 0.6655          | 0.7064   |
| 0.8447        | 4.9   | 38   | 0.4931          | 0.8257   |
| 0.6223        | 5.94  | 46   | 0.3267          | 0.9174   |
| 0.4293        | 6.97  | 54   | 0.4080          | 0.8440   |
| 0.3355        | 8.0   | 62   | 0.1563          | 0.9450   |
| 0.3355        | 8.9   | 69   | 0.1380          | 0.9633   |
| 0.2435        | 9.94  | 77   | 0.1885          | 0.9358   |
| 0.2571        | 10.97 | 85   | 0.1819          | 0.9083   |
| 0.2174        | 12.0  | 93   | 0.1306          | 0.9541   |
| 0.1584        | 12.9  | 100  | 0.0573          | 0.9817   |
| 0.1584        | 13.94 | 108  | 0.1427          | 0.9358   |
| 0.1568        | 14.97 | 116  | 0.1311          | 0.9541   |
| 0.1515        | 16.0  | 124  | 0.1165          | 0.9541   |
| 0.1664        | 16.9  | 131  | 0.0692          | 0.9725   |
| 0.1664        | 17.94 | 139  | 0.0659          | 0.9817   |
| 0.1294        | 18.97 | 147  | 0.1305          | 0.9633   |
| 0.1411        | 20.0  | 155  | 0.0809          | 0.9817   |
| 0.1167        | 20.9  | 162  | 0.0753          | 0.9817   |
| 0.1069        | 21.94 | 170  | 0.0504          | 0.9817   |
| 0.1069        | 22.97 | 178  | 0.0513          | 0.9817   |
| 0.1071        | 24.0  | 186  | 0.0854          | 0.9725   |
| 0.118         | 24.9  | 193  | 0.0816          | 0.9817   |
| 0.094         | 25.94 | 201  | 0.0782          | 0.9817   |
| 0.094         | 26.97 | 209  | 0.1030          | 0.9817   |
| 0.0866        | 28.0  | 217  | 0.0601          | 0.9817   |
| 0.0765        | 28.9  | 224  | 0.0911          | 0.9817   |
| 0.0891        | 29.94 | 232  | 0.0579          | 0.9817   |
| 0.0828        | 30.97 | 240  | 0.0890          | 0.9817   |
| 0.0828        | 32.0  | 248  | 0.0769          | 0.9817   |
| 0.08          | 32.9  | 255  | 0.0668          | 0.9817   |
| 0.0691        | 33.94 | 263  | 0.0807          | 0.9817   |
| 0.082         | 34.97 | 271  | 0.0861          | 0.9817   |
| 0.082         | 36.0  | 279  | 0.0839          | 0.9817   |
| 0.0632        | 36.13 | 280  | 0.0837          | 0.9817   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
