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_fold5
  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: 0.2682926829268293
---

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# hushem_1x_beit_base_sgd_0001_fold5

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: 1.5504
- Accuracy: 0.2683

## 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    | 1.6302          | 0.2439   |
| 1.5748        | 2.0   | 12   | 1.6252          | 0.2439   |
| 1.5748        | 3.0   | 18   | 1.6204          | 0.2439   |
| 1.5763        | 4.0   | 24   | 1.6160          | 0.2439   |
| 1.56          | 5.0   | 30   | 1.6118          | 0.2439   |
| 1.56          | 6.0   | 36   | 1.6079          | 0.2439   |
| 1.5722        | 7.0   | 42   | 1.6043          | 0.2439   |
| 1.5722        | 8.0   | 48   | 1.6006          | 0.2439   |
| 1.5053        | 9.0   | 54   | 1.5970          | 0.2439   |
| 1.5617        | 10.0  | 60   | 1.5937          | 0.2439   |
| 1.5617        | 11.0  | 66   | 1.5908          | 0.2439   |
| 1.5101        | 12.0  | 72   | 1.5876          | 0.2439   |
| 1.5101        | 13.0  | 78   | 1.5848          | 0.2683   |
| 1.5266        | 14.0  | 84   | 1.5820          | 0.2683   |
| 1.4925        | 15.0  | 90   | 1.5796          | 0.2683   |
| 1.4925        | 16.0  | 96   | 1.5771          | 0.2683   |
| 1.5202        | 17.0  | 102  | 1.5750          | 0.2683   |
| 1.5202        | 18.0  | 108  | 1.5729          | 0.2683   |
| 1.5168        | 19.0  | 114  | 1.5711          | 0.2683   |
| 1.5066        | 20.0  | 120  | 1.5691          | 0.2683   |
| 1.5066        | 21.0  | 126  | 1.5674          | 0.2683   |
| 1.508         | 22.0  | 132  | 1.5658          | 0.2683   |
| 1.508         | 23.0  | 138  | 1.5642          | 0.2683   |
| 1.4868        | 24.0  | 144  | 1.5626          | 0.2683   |
| 1.5018        | 25.0  | 150  | 1.5612          | 0.2683   |
| 1.5018        | 26.0  | 156  | 1.5598          | 0.2683   |
| 1.5061        | 27.0  | 162  | 1.5585          | 0.2683   |
| 1.5061        | 28.0  | 168  | 1.5574          | 0.2683   |
| 1.4922        | 29.0  | 174  | 1.5565          | 0.2683   |
| 1.5131        | 30.0  | 180  | 1.5557          | 0.2683   |
| 1.5131        | 31.0  | 186  | 1.5547          | 0.2683   |
| 1.5054        | 32.0  | 192  | 1.5540          | 0.2683   |
| 1.5054        | 33.0  | 198  | 1.5533          | 0.2683   |
| 1.4665        | 34.0  | 204  | 1.5527          | 0.2683   |
| 1.5093        | 35.0  | 210  | 1.5521          | 0.2683   |
| 1.5093        | 36.0  | 216  | 1.5516          | 0.2683   |
| 1.5042        | 37.0  | 222  | 1.5513          | 0.2683   |
| 1.5042        | 38.0  | 228  | 1.5509          | 0.2683   |
| 1.4952        | 39.0  | 234  | 1.5507          | 0.2683   |
| 1.4728        | 40.0  | 240  | 1.5505          | 0.2683   |
| 1.4728        | 41.0  | 246  | 1.5504          | 0.2683   |
| 1.4831        | 42.0  | 252  | 1.5504          | 0.2683   |
| 1.4831        | 43.0  | 258  | 1.5504          | 0.2683   |
| 1.4991        | 44.0  | 264  | 1.5504          | 0.2683   |
| 1.4929        | 45.0  | 270  | 1.5504          | 0.2683   |
| 1.4929        | 46.0  | 276  | 1.5504          | 0.2683   |
| 1.5005        | 47.0  | 282  | 1.5504          | 0.2683   |
| 1.5005        | 48.0  | 288  | 1.5504          | 0.2683   |
| 1.4392        | 49.0  | 294  | 1.5504          | 0.2683   |
| 1.4753        | 50.0  | 300  | 1.5504          | 0.2683   |


### Framework versions

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