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_rms_00001_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: 0.8372093023255814
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hushem_1x_beit_base_rms_00001_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: 0.5862
- Accuracy: 0.8372

## 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: 1e-05
- 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    | 1.3652          | 0.2558   |
| 1.4655        | 2.0   | 12   | 0.9320          | 0.6512   |
| 1.4655        | 3.0   | 18   | 0.5733          | 0.7907   |
| 0.6613        | 4.0   | 24   | 0.3842          | 0.8605   |
| 0.1719        | 5.0   | 30   | 0.4268          | 0.8605   |
| 0.1719        | 6.0   | 36   | 0.3122          | 0.8837   |
| 0.0362        | 7.0   | 42   | 0.5635          | 0.7907   |
| 0.0362        | 8.0   | 48   | 0.2839          | 0.8837   |
| 0.0103        | 9.0   | 54   | 0.3515          | 0.9070   |
| 0.0048        | 10.0  | 60   | 0.4717          | 0.8837   |
| 0.0048        | 11.0  | 66   | 0.4775          | 0.8372   |
| 0.0038        | 12.0  | 72   | 0.5321          | 0.7907   |
| 0.0038        | 13.0  | 78   | 0.4659          | 0.8372   |
| 0.0022        | 14.0  | 84   | 0.5318          | 0.8140   |
| 0.0017        | 15.0  | 90   | 0.5328          | 0.8605   |
| 0.0017        | 16.0  | 96   | 0.4991          | 0.8372   |
| 0.0025        | 17.0  | 102  | 0.5203          | 0.8372   |
| 0.0025        | 18.0  | 108  | 0.5439          | 0.8372   |
| 0.0011        | 19.0  | 114  | 0.5049          | 0.8372   |
| 0.0014        | 20.0  | 120  | 0.5023          | 0.8372   |
| 0.0014        | 21.0  | 126  | 0.5748          | 0.8372   |
| 0.0013        | 22.0  | 132  | 0.5341          | 0.8372   |
| 0.0013        | 23.0  | 138  | 0.4866          | 0.8372   |
| 0.0011        | 24.0  | 144  | 0.5270          | 0.8372   |
| 0.0012        | 25.0  | 150  | 0.5889          | 0.8372   |
| 0.0012        | 26.0  | 156  | 0.6180          | 0.8372   |
| 0.0013        | 27.0  | 162  | 0.6227          | 0.8372   |
| 0.0013        | 28.0  | 168  | 0.6125          | 0.8372   |
| 0.0007        | 29.0  | 174  | 0.5708          | 0.8605   |
| 0.0004        | 30.0  | 180  | 0.5729          | 0.8372   |
| 0.0004        | 31.0  | 186  | 0.5789          | 0.8372   |
| 0.001         | 32.0  | 192  | 0.5842          | 0.8140   |
| 0.001         | 33.0  | 198  | 0.5989          | 0.8372   |
| 0.0008        | 34.0  | 204  | 0.5775          | 0.8140   |
| 0.0013        | 35.0  | 210  | 0.5738          | 0.8372   |
| 0.0013        | 36.0  | 216  | 0.5742          | 0.8140   |
| 0.0006        | 37.0  | 222  | 0.6172          | 0.8140   |
| 0.0006        | 38.0  | 228  | 0.5958          | 0.8140   |
| 0.0026        | 39.0  | 234  | 0.5884          | 0.8140   |
| 0.0006        | 40.0  | 240  | 0.5885          | 0.8140   |
| 0.0006        | 41.0  | 246  | 0.5863          | 0.8372   |
| 0.0008        | 42.0  | 252  | 0.5862          | 0.8372   |
| 0.0008        | 43.0  | 258  | 0.5862          | 0.8372   |
| 0.0006        | 44.0  | 264  | 0.5862          | 0.8372   |
| 0.0004        | 45.0  | 270  | 0.5862          | 0.8372   |
| 0.0004        | 46.0  | 276  | 0.5862          | 0.8372   |
| 0.0006        | 47.0  | 282  | 0.5862          | 0.8372   |
| 0.0006        | 48.0  | 288  | 0.5862          | 0.8372   |
| 0.0005        | 49.0  | 294  | 0.5862          | 0.8372   |
| 0.0004        | 50.0  | 300  | 0.5862          | 0.8372   |


### Framework versions

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