---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-OT-alt
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9032258064516129
---

<!-- 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-OT-alt

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: 0.4274
- Accuracy: 0.9032

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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        | 0.91  | 5    | 1.7093          | 0.1774   |
| 1.7744        | 2.0   | 11   | 1.6178          | 0.1774   |
| 1.7744        | 2.91  | 16   | 1.4730          | 0.1774   |
| 1.5823        | 4.0   | 22   | 1.2754          | 0.1774   |
| 1.5823        | 4.91  | 27   | 1.1455          | 0.5645   |
| 1.27          | 6.0   | 33   | 1.0147          | 0.6290   |
| 1.27          | 6.91  | 38   | 0.9790          | 0.5484   |
| 1.079         | 8.0   | 44   | 1.0474          | 0.4516   |
| 1.079         | 8.91  | 49   | 0.8796          | 0.7581   |
| 1.005         | 10.0  | 55   | 0.7759          | 0.7742   |
| 0.8479        | 10.91 | 60   | 0.7421          | 0.8226   |
| 0.8479        | 12.0  | 66   | 0.6760          | 0.8548   |
| 0.7695        | 12.91 | 71   | 0.5933          | 0.8387   |
| 0.7695        | 14.0  | 77   | 0.6372          | 0.7742   |
| 0.6591        | 14.91 | 82   | 0.5653          | 0.8387   |
| 0.6591        | 16.0  | 88   | 0.4950          | 0.8710   |
| 0.5675        | 16.91 | 93   | 0.5040          | 0.8226   |
| 0.5675        | 18.0  | 99   | 0.4274          | 0.9032   |
| 0.5134        | 18.91 | 104  | 0.4617          | 0.8548   |
| 0.4418        | 20.0  | 110  | 0.4245          | 0.8871   |
| 0.4418        | 20.91 | 115  | 0.4922          | 0.8387   |
| 0.402         | 22.0  | 121  | 0.5112          | 0.8226   |
| 0.402         | 22.91 | 126  | 0.4696          | 0.8548   |
| 0.4039        | 24.0  | 132  | 0.4014          | 0.8710   |
| 0.4039        | 24.91 | 137  | 0.5006          | 0.8226   |
| 0.4216        | 26.0  | 143  | 0.5351          | 0.8548   |
| 0.4216        | 26.91 | 148  | 0.5203          | 0.8548   |
| 0.3593        | 28.0  | 154  | 0.4082          | 0.8548   |
| 0.3593        | 28.91 | 159  | 0.4017          | 0.8710   |
| 0.3638        | 30.0  | 165  | 0.4068          | 0.8871   |
| 0.3509        | 30.91 | 170  | 0.3991          | 0.8871   |
| 0.3509        | 32.0  | 176  | 0.3965          | 0.8710   |
| 0.3426        | 32.91 | 181  | 0.3921          | 0.8710   |
| 0.3426        | 34.0  | 187  | 0.3998          | 0.8710   |
| 0.3253        | 34.91 | 192  | 0.4102          | 0.8871   |
| 0.3253        | 36.0  | 198  | 0.4081          | 0.8871   |
| 0.3085        | 36.36 | 200  | 0.4083          | 0.8871   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0