transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
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_0001_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: 0.1111111111111111
---

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# hushem_1x_beit_base_sgd_0001_fold1

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: 1.6388
- Accuracy: 0.1111

## 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: 0.0001
- 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    | 1.6742          | 0.1111   |
| 1.4975        | 2.0   | 12   | 1.6721          | 0.1111   |
| 1.4975        | 3.0   | 18   | 1.6701          | 0.1111   |
| 1.4871        | 4.0   | 24   | 1.6683          | 0.1111   |
| 1.4949        | 5.0   | 30   | 1.6664          | 0.1111   |
| 1.4949        | 6.0   | 36   | 1.6646          | 0.1111   |
| 1.4943        | 7.0   | 42   | 1.6628          | 0.1111   |
| 1.4943        | 8.0   | 48   | 1.6613          | 0.1111   |
| 1.5225        | 9.0   | 54   | 1.6596          | 0.1111   |
| 1.4389        | 10.0  | 60   | 1.6582          | 0.1111   |
| 1.4389        | 11.0  | 66   | 1.6569          | 0.1111   |
| 1.4732        | 12.0  | 72   | 1.6557          | 0.1111   |
| 1.4732        | 13.0  | 78   | 1.6545          | 0.1111   |
| 1.4384        | 14.0  | 84   | 1.6534          | 0.1111   |
| 1.4676        | 15.0  | 90   | 1.6523          | 0.1111   |
| 1.4676        | 16.0  | 96   | 1.6513          | 0.1111   |
| 1.4696        | 17.0  | 102  | 1.6502          | 0.1111   |
| 1.4696        | 18.0  | 108  | 1.6492          | 0.1111   |
| 1.4688        | 19.0  | 114  | 1.6483          | 0.1111   |
| 1.4525        | 20.0  | 120  | 1.6474          | 0.1111   |
| 1.4525        | 21.0  | 126  | 1.6467          | 0.1111   |
| 1.4642        | 22.0  | 132  | 1.6459          | 0.1111   |
| 1.4642        | 23.0  | 138  | 1.6451          | 0.1111   |
| 1.4184        | 24.0  | 144  | 1.6445          | 0.1111   |
| 1.4687        | 25.0  | 150  | 1.6439          | 0.1111   |
| 1.4687        | 26.0  | 156  | 1.6433          | 0.1111   |
| 1.4512        | 27.0  | 162  | 1.6428          | 0.1111   |
| 1.4512        | 28.0  | 168  | 1.6422          | 0.1111   |
| 1.4747        | 29.0  | 174  | 1.6417          | 0.1111   |
| 1.4313        | 30.0  | 180  | 1.6412          | 0.1111   |
| 1.4313        | 31.0  | 186  | 1.6408          | 0.1111   |
| 1.4333        | 32.0  | 192  | 1.6405          | 0.1111   |
| 1.4333        | 33.0  | 198  | 1.6401          | 0.1111   |
| 1.4855        | 34.0  | 204  | 1.6398          | 0.1111   |
| 1.4466        | 35.0  | 210  | 1.6396          | 0.1111   |
| 1.4466        | 36.0  | 216  | 1.6394          | 0.1111   |
| 1.4336        | 37.0  | 222  | 1.6392          | 0.1111   |
| 1.4336        | 38.0  | 228  | 1.6390          | 0.1111   |
| 1.4754        | 39.0  | 234  | 1.6389          | 0.1111   |
| 1.4452        | 40.0  | 240  | 1.6388          | 0.1111   |
| 1.4452        | 41.0  | 246  | 1.6388          | 0.1111   |
| 1.4335        | 42.0  | 252  | 1.6388          | 0.1111   |
| 1.4335        | 43.0  | 258  | 1.6388          | 0.1111   |
| 1.4391        | 44.0  | 264  | 1.6388          | 0.1111   |
| 1.4625        | 45.0  | 270  | 1.6388          | 0.1111   |
| 1.4625        | 46.0  | 276  | 1.6388          | 0.1111   |
| 1.4619        | 47.0  | 282  | 1.6388          | 0.1111   |
| 1.4619        | 48.0  | 288  | 1.6388          | 0.1111   |
| 1.4316        | 49.0  | 294  | 1.6388          | 0.1111   |
| 1.4278        | 50.0  | 300  | 1.6388          | 0.1111   |


### Framework versions

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