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_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: 0.4222222222222222
---

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# hushem_1x_beit_base_rms_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: 1.5076
- Accuracy: 0.4222

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 3.8156          | 0.2444   |
| 3.6272        | 2.0   | 12   | 1.5830          | 0.2444   |
| 3.6272        | 3.0   | 18   | 1.3920          | 0.3556   |
| 1.5643        | 4.0   | 24   | 1.3724          | 0.4667   |
| 1.4312        | 5.0   | 30   | 1.3703          | 0.4      |
| 1.4312        | 6.0   | 36   | 1.5314          | 0.2444   |
| 1.3956        | 7.0   | 42   | 1.3355          | 0.3111   |
| 1.3956        | 8.0   | 48   | 1.4411          | 0.3111   |
| 1.3396        | 9.0   | 54   | 1.4040          | 0.2667   |
| 1.3553        | 10.0  | 60   | 1.2838          | 0.5111   |
| 1.3553        | 11.0  | 66   | 1.2321          | 0.4889   |
| 1.3209        | 12.0  | 72   | 1.1729          | 0.4667   |
| 1.3209        | 13.0  | 78   | 1.2333          | 0.3556   |
| 1.2531        | 14.0  | 84   | 1.5215          | 0.3111   |
| 1.2528        | 15.0  | 90   | 1.2938          | 0.3778   |
| 1.2528        | 16.0  | 96   | 1.3032          | 0.3333   |
| 1.2233        | 17.0  | 102  | 1.2266          | 0.4667   |
| 1.2233        | 18.0  | 108  | 1.4102          | 0.3778   |
| 1.176         | 19.0  | 114  | 1.5633          | 0.2889   |
| 1.185         | 20.0  | 120  | 1.2459          | 0.4444   |
| 1.185         | 21.0  | 126  | 1.2338          | 0.4444   |
| 1.1231        | 22.0  | 132  | 1.2463          | 0.3333   |
| 1.1231        | 23.0  | 138  | 1.1738          | 0.5333   |
| 1.1314        | 24.0  | 144  | 1.3614          | 0.3778   |
| 1.083         | 25.0  | 150  | 1.1802          | 0.5556   |
| 1.083         | 26.0  | 156  | 1.2064          | 0.4444   |
| 1.0558        | 27.0  | 162  | 1.2033          | 0.5111   |
| 1.0558        | 28.0  | 168  | 1.2614          | 0.4444   |
| 1.0238        | 29.0  | 174  | 1.1933          | 0.4667   |
| 1.0431        | 30.0  | 180  | 1.2411          | 0.3333   |
| 1.0431        | 31.0  | 186  | 1.1551          | 0.5111   |
| 0.9703        | 32.0  | 192  | 1.2204          | 0.5778   |
| 0.9703        | 33.0  | 198  | 1.2367          | 0.4667   |
| 0.9502        | 34.0  | 204  | 1.2552          | 0.4222   |
| 0.8685        | 35.0  | 210  | 1.2938          | 0.4889   |
| 0.8685        | 36.0  | 216  | 1.3314          | 0.4889   |
| 0.8441        | 37.0  | 222  | 1.4307          | 0.5111   |
| 0.8441        | 38.0  | 228  | 1.3667          | 0.5111   |
| 0.7558        | 39.0  | 234  | 1.4572          | 0.4444   |
| 0.7537        | 40.0  | 240  | 1.4773          | 0.4667   |
| 0.7537        | 41.0  | 246  | 1.5046          | 0.4222   |
| 0.7017        | 42.0  | 252  | 1.5076          | 0.4222   |
| 0.7017        | 43.0  | 258  | 1.5076          | 0.4222   |
| 0.7145        | 44.0  | 264  | 1.5076          | 0.4222   |
| 0.7028        | 45.0  | 270  | 1.5076          | 0.4222   |
| 0.7028        | 46.0  | 276  | 1.5076          | 0.4222   |
| 0.6738        | 47.0  | 282  | 1.5076          | 0.4222   |
| 0.6738        | 48.0  | 288  | 1.5076          | 0.4222   |
| 0.7171        | 49.0  | 294  | 1.5076          | 0.4222   |
| 0.6462        | 50.0  | 300  | 1.5076          | 0.4222   |


### Framework versions

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