---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_10x_beit_large_adamax_001_fold1
  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: 0.9048414023372288
---

<!-- 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. -->

# smids_10x_beit_large_adamax_001_fold1

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9751
- Accuracy: 0.9048

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3471        | 1.0   | 751   | 0.3720          | 0.8631   |
| 0.2879        | 2.0   | 1502  | 0.4078          | 0.8364   |
| 0.2355        | 3.0   | 2253  | 0.4002          | 0.8831   |
| 0.2335        | 4.0   | 3004  | 0.2992          | 0.8831   |
| 0.1816        | 5.0   | 3755  | 0.3290          | 0.8965   |
| 0.1386        | 6.0   | 4506  | 0.3986          | 0.8898   |
| 0.1637        | 7.0   | 5257  | 0.4542          | 0.8681   |
| 0.0627        | 8.0   | 6008  | 0.4567          | 0.8965   |
| 0.0985        | 9.0   | 6759  | 0.3926          | 0.9015   |
| 0.1363        | 10.0  | 7510  | 0.4519          | 0.8848   |
| 0.0463        | 11.0  | 8261  | 0.5853          | 0.8898   |
| 0.023         | 12.0  | 9012  | 0.5711          | 0.8865   |
| 0.0292        | 13.0  | 9763  | 0.5829          | 0.8932   |
| 0.0137        | 14.0  | 10514 | 0.5739          | 0.8965   |
| 0.0034        | 15.0  | 11265 | 0.6922          | 0.8815   |
| 0.0201        | 16.0  | 12016 | 0.6833          | 0.8948   |
| 0.0068        | 17.0  | 12767 | 0.7845          | 0.8898   |
| 0.0084        | 18.0  | 13518 | 0.6851          | 0.8781   |
| 0.0033        | 19.0  | 14269 | 0.6219          | 0.8998   |
| 0.0023        | 20.0  | 15020 | 0.5986          | 0.8982   |
| 0.0011        | 21.0  | 15771 | 0.6825          | 0.8965   |
| 0.0011        | 22.0  | 16522 | 0.7971          | 0.8932   |
| 0.027         | 23.0  | 17273 | 0.5546          | 0.9098   |
| 0.0061        | 24.0  | 18024 | 0.6400          | 0.8932   |
| 0.0001        | 25.0  | 18775 | 0.6875          | 0.8965   |
| 0.0111        | 26.0  | 19526 | 0.7316          | 0.8965   |
| 0.0029        | 27.0  | 20277 | 0.8142          | 0.8865   |
| 0.0004        | 28.0  | 21028 | 0.7441          | 0.8915   |
| 0.0043        | 29.0  | 21779 | 0.7052          | 0.8965   |
| 0.0           | 30.0  | 22530 | 0.7049          | 0.9048   |
| 0.0           | 31.0  | 23281 | 0.8253          | 0.9149   |
| 0.0005        | 32.0  | 24032 | 0.6696          | 0.9065   |
| 0.0001        | 33.0  | 24783 | 0.8050          | 0.9065   |
| 0.0           | 34.0  | 25534 | 0.8833          | 0.9015   |
| 0.0           | 35.0  | 26285 | 0.8344          | 0.9032   |
| 0.0           | 36.0  | 27036 | 0.8190          | 0.8982   |
| 0.0           | 37.0  | 27787 | 0.8357          | 0.9032   |
| 0.0           | 38.0  | 28538 | 0.9401          | 0.9015   |
| 0.0           | 39.0  | 29289 | 0.7726          | 0.9115   |
| 0.0           | 40.0  | 30040 | 0.8975          | 0.8965   |
| 0.0           | 41.0  | 30791 | 0.8489          | 0.9065   |
| 0.0           | 42.0  | 31542 | 0.9519          | 0.8998   |
| 0.0           | 43.0  | 32293 | 0.9084          | 0.9032   |
| 0.0           | 44.0  | 33044 | 0.9097          | 0.9048   |
| 0.0           | 45.0  | 33795 | 0.9438          | 0.9098   |
| 0.0           | 46.0  | 34546 | 0.9461          | 0.9082   |
| 0.0           | 47.0  | 35297 | 0.9632          | 0.9048   |
| 0.0           | 48.0  | 36048 | 0.9598          | 0.9065   |
| 0.0           | 49.0  | 36799 | 0.9723          | 0.9048   |
| 0.0           | 50.0  | 37550 | 0.9751          | 0.9048   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2