---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_beit_base_adamax_001_fold2
  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: 0.7903494176372712
---

<!-- 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_1x_beit_base_adamax_001_fold2

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: 1.4865
- Accuracy: 0.7903

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9007        | 1.0   | 75   | 0.8802          | 0.5191   |
| 0.7789        | 2.0   | 150  | 0.8973          | 0.5424   |
| 0.8219        | 3.0   | 225  | 0.7607          | 0.6406   |
| 0.7838        | 4.0   | 300  | 0.7358          | 0.6522   |
| 0.6602        | 5.0   | 375  | 0.6978          | 0.6672   |
| 0.7026        | 6.0   | 450  | 0.6685          | 0.6955   |
| 0.6394        | 7.0   | 525  | 0.7731          | 0.6589   |
| 0.6471        | 8.0   | 600  | 0.6234          | 0.7138   |
| 0.5881        | 9.0   | 675  | 0.6358          | 0.7205   |
| 0.5254        | 10.0  | 750  | 0.5746          | 0.7671   |
| 0.5153        | 11.0  | 825  | 0.5501          | 0.7704   |
| 0.5459        | 12.0  | 900  | 0.5543          | 0.7687   |
| 0.5526        | 13.0  | 975  | 0.5321          | 0.7737   |
| 0.5236        | 14.0  | 1050 | 0.5404          | 0.7937   |
| 0.4317        | 15.0  | 1125 | 0.6220          | 0.7604   |
| 0.4195        | 16.0  | 1200 | 0.5679          | 0.7854   |
| 0.3753        | 17.0  | 1275 | 0.6021          | 0.7687   |
| 0.3821        | 18.0  | 1350 | 0.5958          | 0.7854   |
| 0.3599        | 19.0  | 1425 | 0.6478          | 0.7837   |
| 0.2813        | 20.0  | 1500 | 0.6634          | 0.7671   |
| 0.224         | 21.0  | 1575 | 0.6766          | 0.7820   |
| 0.2635        | 22.0  | 1650 | 0.6781          | 0.7870   |
| 0.1832        | 23.0  | 1725 | 0.8041          | 0.7604   |
| 0.1751        | 24.0  | 1800 | 0.8069          | 0.7671   |
| 0.2421        | 25.0  | 1875 | 0.8820          | 0.7737   |
| 0.2115        | 26.0  | 1950 | 0.8838          | 0.7970   |
| 0.1798        | 27.0  | 2025 | 0.8954          | 0.7787   |
| 0.1341        | 28.0  | 2100 | 1.0505          | 0.7987   |
| 0.0669        | 29.0  | 2175 | 1.2992          | 0.7770   |
| 0.0892        | 30.0  | 2250 | 1.1168          | 0.7987   |
| 0.1159        | 31.0  | 2325 | 1.2066          | 0.7870   |
| 0.1289        | 32.0  | 2400 | 1.5859          | 0.7687   |
| 0.0687        | 33.0  | 2475 | 1.1777          | 0.7887   |
| 0.0226        | 34.0  | 2550 | 1.4423          | 0.7854   |
| 0.04          | 35.0  | 2625 | 1.4594          | 0.7870   |
| 0.0552        | 36.0  | 2700 | 1.3867          | 0.7820   |
| 0.0439        | 37.0  | 2775 | 1.4599          | 0.7720   |
| 0.0308        | 38.0  | 2850 | 1.4968          | 0.7903   |
| 0.0564        | 39.0  | 2925 | 1.5256          | 0.7953   |
| 0.0227        | 40.0  | 3000 | 1.4454          | 0.7953   |
| 0.0214        | 41.0  | 3075 | 1.3100          | 0.8087   |
| 0.0167        | 42.0  | 3150 | 1.4699          | 0.7987   |
| 0.0299        | 43.0  | 3225 | 1.4525          | 0.7903   |
| 0.0171        | 44.0  | 3300 | 1.3889          | 0.8053   |
| 0.011         | 45.0  | 3375 | 1.3819          | 0.7920   |
| 0.014         | 46.0  | 3450 | 1.5122          | 0.7903   |
| 0.0198        | 47.0  | 3525 | 1.4328          | 0.7920   |
| 0.0085        | 48.0  | 3600 | 1.5057          | 0.7920   |
| 0.0028        | 49.0  | 3675 | 1.4856          | 0.7903   |
| 0.0049        | 50.0  | 3750 | 1.4865          | 0.7903   |


### Framework versions

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