---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_beit_base_sgd_001_fold3
  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: 0.3023255813953488
---

<!-- 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_1x_beit_base_sgd_001_fold3

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co./microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3325
- Accuracy: 0.3023

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.5424          | 0.2558   |
| 1.5472        | 2.0   | 12   | 1.5114          | 0.2326   |
| 1.5472        | 3.0   | 18   | 1.4888          | 0.2791   |
| 1.4947        | 4.0   | 24   | 1.4715          | 0.2558   |
| 1.4055        | 5.0   | 30   | 1.4594          | 0.2791   |
| 1.4055        | 6.0   | 36   | 1.4478          | 0.3256   |
| 1.389         | 7.0   | 42   | 1.4378          | 0.3023   |
| 1.389         | 8.0   | 48   | 1.4298          | 0.3256   |
| 1.3593        | 9.0   | 54   | 1.4226          | 0.3488   |
| 1.3527        | 10.0  | 60   | 1.4160          | 0.3488   |
| 1.3527        | 11.0  | 66   | 1.4104          | 0.3488   |
| 1.3352        | 12.0  | 72   | 1.4055          | 0.3488   |
| 1.3352        | 13.0  | 78   | 1.4005          | 0.3721   |
| 1.2989        | 14.0  | 84   | 1.3949          | 0.3721   |
| 1.3078        | 15.0  | 90   | 1.3896          | 0.3721   |
| 1.3078        | 16.0  | 96   | 1.3853          | 0.3721   |
| 1.2945        | 17.0  | 102  | 1.3807          | 0.3488   |
| 1.2945        | 18.0  | 108  | 1.3772          | 0.3721   |
| 1.2862        | 19.0  | 114  | 1.3730          | 0.3488   |
| 1.2665        | 20.0  | 120  | 1.3692          | 0.3488   |
| 1.2665        | 21.0  | 126  | 1.3663          | 0.3488   |
| 1.2571        | 22.0  | 132  | 1.3633          | 0.3488   |
| 1.2571        | 23.0  | 138  | 1.3594          | 0.3488   |
| 1.2478        | 24.0  | 144  | 1.3564          | 0.3488   |
| 1.2356        | 25.0  | 150  | 1.3537          | 0.3488   |
| 1.2356        | 26.0  | 156  | 1.3506          | 0.3256   |
| 1.253         | 27.0  | 162  | 1.3489          | 0.3256   |
| 1.253         | 28.0  | 168  | 1.3460          | 0.3256   |
| 1.2445        | 29.0  | 174  | 1.3442          | 0.3256   |
| 1.208         | 30.0  | 180  | 1.3430          | 0.3023   |
| 1.208         | 31.0  | 186  | 1.3417          | 0.3256   |
| 1.204         | 32.0  | 192  | 1.3396          | 0.3023   |
| 1.204         | 33.0  | 198  | 1.3381          | 0.3023   |
| 1.1994        | 34.0  | 204  | 1.3371          | 0.3023   |
| 1.1991        | 35.0  | 210  | 1.3357          | 0.3023   |
| 1.1991        | 36.0  | 216  | 1.3349          | 0.3023   |
| 1.1819        | 37.0  | 222  | 1.3343          | 0.3023   |
| 1.1819        | 38.0  | 228  | 1.3338          | 0.3023   |
| 1.1973        | 39.0  | 234  | 1.3332          | 0.3023   |
| 1.1899        | 40.0  | 240  | 1.3328          | 0.3023   |
| 1.1899        | 41.0  | 246  | 1.3326          | 0.3023   |
| 1.1779        | 42.0  | 252  | 1.3325          | 0.3023   |
| 1.1779        | 43.0  | 258  | 1.3325          | 0.3023   |
| 1.1962        | 44.0  | 264  | 1.3325          | 0.3023   |
| 1.2031        | 45.0  | 270  | 1.3325          | 0.3023   |
| 1.2031        | 46.0  | 276  | 1.3325          | 0.3023   |
| 1.1985        | 47.0  | 282  | 1.3325          | 0.3023   |
| 1.1985        | 48.0  | 288  | 1.3325          | 0.3023   |
| 1.1942        | 49.0  | 294  | 1.3325          | 0.3023   |
| 1.1653        | 50.0  | 300  | 1.3325          | 0.3023   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0