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: smids_1x_beit_base_sgd_001_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: 0.8647746243739566
---

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# smids_1x_beit_base_sgd_001_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: 0.3272
- Accuracy: 0.8648

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.023         | 1.0   | 76   | 0.9338          | 0.5960   |
| 0.8695        | 2.0   | 152  | 0.7961          | 0.6962   |
| 0.7472        | 3.0   | 228  | 0.7107          | 0.7245   |
| 0.6931        | 4.0   | 304  | 0.6455          | 0.7579   |
| 0.6024        | 5.0   | 380  | 0.6009          | 0.7830   |
| 0.5887        | 6.0   | 456  | 0.5575          | 0.7896   |
| 0.5612        | 7.0   | 532  | 0.5303          | 0.7947   |
| 0.5261        | 8.0   | 608  | 0.5077          | 0.8197   |
| 0.5291        | 9.0   | 684  | 0.4867          | 0.8164   |
| 0.4139        | 10.0  | 760  | 0.4652          | 0.8230   |
| 0.4709        | 11.0  | 836  | 0.4493          | 0.8264   |
| 0.4127        | 12.0  | 912  | 0.4359          | 0.8397   |
| 0.419         | 13.0  | 988  | 0.4224          | 0.8381   |
| 0.4108        | 14.0  | 1064 | 0.4104          | 0.8481   |
| 0.5096        | 15.0  | 1140 | 0.4034          | 0.8497   |
| 0.4428        | 16.0  | 1216 | 0.3953          | 0.8548   |
| 0.4039        | 17.0  | 1292 | 0.3903          | 0.8598   |
| 0.3283        | 18.0  | 1368 | 0.3811          | 0.8598   |
| 0.4203        | 19.0  | 1444 | 0.3747          | 0.8681   |
| 0.449         | 20.0  | 1520 | 0.3742          | 0.8631   |
| 0.3886        | 21.0  | 1596 | 0.3668          | 0.8631   |
| 0.3947        | 22.0  | 1672 | 0.3711          | 0.8631   |
| 0.3271        | 23.0  | 1748 | 0.3637          | 0.8564   |
| 0.3744        | 24.0  | 1824 | 0.3594          | 0.8631   |
| 0.3021        | 25.0  | 1900 | 0.3558          | 0.8614   |
| 0.3505        | 26.0  | 1976 | 0.3515          | 0.8631   |
| 0.2842        | 27.0  | 2052 | 0.3497          | 0.8648   |
| 0.3503        | 28.0  | 2128 | 0.3458          | 0.8698   |
| 0.3076        | 29.0  | 2204 | 0.3443          | 0.8664   |
| 0.3164        | 30.0  | 2280 | 0.3411          | 0.8648   |
| 0.3293        | 31.0  | 2356 | 0.3409          | 0.8631   |
| 0.3108        | 32.0  | 2432 | 0.3378          | 0.8648   |
| 0.2993        | 33.0  | 2508 | 0.3374          | 0.8648   |
| 0.3123        | 34.0  | 2584 | 0.3356          | 0.8648   |
| 0.4733        | 35.0  | 2660 | 0.3344          | 0.8664   |
| 0.3442        | 36.0  | 2736 | 0.3328          | 0.8681   |
| 0.3357        | 37.0  | 2812 | 0.3329          | 0.8648   |
| 0.2903        | 38.0  | 2888 | 0.3325          | 0.8698   |
| 0.2981        | 39.0  | 2964 | 0.3300          | 0.8681   |
| 0.3433        | 40.0  | 3040 | 0.3301          | 0.8664   |
| 0.2756        | 41.0  | 3116 | 0.3304          | 0.8648   |
| 0.3213        | 42.0  | 3192 | 0.3307          | 0.8631   |
| 0.2954        | 43.0  | 3268 | 0.3290          | 0.8664   |
| 0.3403        | 44.0  | 3344 | 0.3293          | 0.8648   |
| 0.3019        | 45.0  | 3420 | 0.3281          | 0.8664   |
| 0.267         | 46.0  | 3496 | 0.3277          | 0.8664   |
| 0.3291        | 47.0  | 3572 | 0.3275          | 0.8664   |
| 0.2958        | 48.0  | 3648 | 0.3273          | 0.8664   |
| 0.2907        | 49.0  | 3724 | 0.3272          | 0.8648   |
| 0.2994        | 50.0  | 3800 | 0.3272          | 0.8648   |


### Framework versions

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