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---
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_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: 0.3333333333333333
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hushem_1x_beit_base_sgd_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: 1.2883
- Accuracy: 0.3333
## 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 | 1.5095 | 0.2667 |
| 1.5706 | 2.0 | 12 | 1.4767 | 0.2667 |
| 1.5706 | 3.0 | 18 | 1.4520 | 0.2667 |
| 1.4609 | 4.0 | 24 | 1.4339 | 0.3111 |
| 1.4723 | 5.0 | 30 | 1.4175 | 0.3111 |
| 1.4723 | 6.0 | 36 | 1.4043 | 0.3111 |
| 1.4256 | 7.0 | 42 | 1.3928 | 0.3111 |
| 1.4256 | 8.0 | 48 | 1.3810 | 0.3111 |
| 1.3951 | 9.0 | 54 | 1.3717 | 0.3111 |
| 1.359 | 10.0 | 60 | 1.3630 | 0.3111 |
| 1.359 | 11.0 | 66 | 1.3563 | 0.3111 |
| 1.3542 | 12.0 | 72 | 1.3514 | 0.2889 |
| 1.3542 | 13.0 | 78 | 1.3444 | 0.2889 |
| 1.3277 | 14.0 | 84 | 1.3408 | 0.2667 |
| 1.3111 | 15.0 | 90 | 1.3350 | 0.2667 |
| 1.3111 | 16.0 | 96 | 1.3320 | 0.2889 |
| 1.3054 | 17.0 | 102 | 1.3278 | 0.2889 |
| 1.3054 | 18.0 | 108 | 1.3233 | 0.2889 |
| 1.2953 | 19.0 | 114 | 1.3199 | 0.2889 |
| 1.2867 | 20.0 | 120 | 1.3171 | 0.2889 |
| 1.2867 | 21.0 | 126 | 1.3151 | 0.2889 |
| 1.2581 | 22.0 | 132 | 1.3144 | 0.2889 |
| 1.2581 | 23.0 | 138 | 1.3095 | 0.2889 |
| 1.2646 | 24.0 | 144 | 1.3068 | 0.3111 |
| 1.2188 | 25.0 | 150 | 1.3045 | 0.3111 |
| 1.2188 | 26.0 | 156 | 1.3025 | 0.3333 |
| 1.2206 | 27.0 | 162 | 1.3017 | 0.3333 |
| 1.2206 | 28.0 | 168 | 1.2992 | 0.3333 |
| 1.2061 | 29.0 | 174 | 1.2990 | 0.3333 |
| 1.2221 | 30.0 | 180 | 1.2969 | 0.3333 |
| 1.2221 | 31.0 | 186 | 1.2951 | 0.3333 |
| 1.2025 | 32.0 | 192 | 1.2945 | 0.3333 |
| 1.2025 | 33.0 | 198 | 1.2933 | 0.3333 |
| 1.2187 | 34.0 | 204 | 1.2926 | 0.3333 |
| 1.2089 | 35.0 | 210 | 1.2913 | 0.3333 |
| 1.2089 | 36.0 | 216 | 1.2899 | 0.3333 |
| 1.1998 | 37.0 | 222 | 1.2891 | 0.3333 |
| 1.1998 | 38.0 | 228 | 1.2890 | 0.3333 |
| 1.2017 | 39.0 | 234 | 1.2884 | 0.3333 |
| 1.1887 | 40.0 | 240 | 1.2883 | 0.3333 |
| 1.1887 | 41.0 | 246 | 1.2883 | 0.3333 |
| 1.1807 | 42.0 | 252 | 1.2883 | 0.3333 |
| 1.1807 | 43.0 | 258 | 1.2883 | 0.3333 |
| 1.2122 | 44.0 | 264 | 1.2883 | 0.3333 |
| 1.2003 | 45.0 | 270 | 1.2883 | 0.3333 |
| 1.2003 | 46.0 | 276 | 1.2883 | 0.3333 |
| 1.1882 | 47.0 | 282 | 1.2883 | 0.3333 |
| 1.1882 | 48.0 | 288 | 1.2883 | 0.3333 |
| 1.1992 | 49.0 | 294 | 1.2883 | 0.3333 |
| 1.1934 | 50.0 | 300 | 1.2883 | 0.3333 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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