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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: BEiT-RHS-NDA
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8317757009345794
---
<!-- 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. -->
# BEiT-RHS-NDA
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: 0.5322
- Accuracy: 0.8318
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 8 | 0.6851 | 0.5888 |
| 0.6911 | 2.0 | 16 | 0.6721 | 0.5888 |
| 0.6739 | 3.0 | 24 | 0.6504 | 0.5888 |
| 0.6595 | 4.0 | 32 | 0.6432 | 0.5888 |
| 0.646 | 5.0 | 40 | 0.6317 | 0.6822 |
| 0.646 | 6.0 | 48 | 0.6175 | 0.6916 |
| 0.6142 | 7.0 | 56 | 0.6270 | 0.6916 |
| 0.608 | 8.0 | 64 | 0.6618 | 0.6916 |
| 0.5927 | 9.0 | 72 | 0.5347 | 0.6916 |
| 0.5333 | 10.0 | 80 | 0.5744 | 0.6449 |
| 0.5333 | 11.0 | 88 | 0.4974 | 0.7477 |
| 0.4987 | 12.0 | 96 | 0.5970 | 0.6449 |
| 0.5421 | 13.0 | 104 | 0.5137 | 0.7383 |
| 0.4881 | 14.0 | 112 | 0.4727 | 0.7664 |
| 0.4408 | 15.0 | 120 | 0.5161 | 0.7664 |
| 0.4408 | 16.0 | 128 | 0.6732 | 0.6916 |
| 0.4923 | 17.0 | 136 | 0.6568 | 0.7009 |
| 0.4135 | 18.0 | 144 | 0.6653 | 0.7009 |
| 0.4308 | 19.0 | 152 | 0.6032 | 0.7196 |
| 0.3837 | 20.0 | 160 | 0.4492 | 0.8037 |
| 0.3837 | 21.0 | 168 | 0.4549 | 0.7944 |
| 0.3297 | 22.0 | 176 | 0.5526 | 0.7664 |
| 0.3264 | 23.0 | 184 | 0.5172 | 0.7944 |
| 0.3487 | 24.0 | 192 | 0.5105 | 0.7664 |
| 0.2892 | 25.0 | 200 | 0.4566 | 0.7757 |
| 0.2892 | 26.0 | 208 | 0.5233 | 0.7944 |
| 0.2505 | 27.0 | 216 | 0.4817 | 0.7944 |
| 0.2542 | 28.0 | 224 | 0.5035 | 0.8037 |
| 0.2285 | 29.0 | 232 | 0.5282 | 0.7944 |
| 0.2053 | 30.0 | 240 | 0.5638 | 0.8131 |
| 0.2053 | 31.0 | 248 | 0.6190 | 0.7570 |
| 0.2205 | 32.0 | 256 | 0.6142 | 0.7850 |
| 0.2081 | 33.0 | 264 | 0.5752 | 0.7850 |
| 0.2075 | 34.0 | 272 | 0.5322 | 0.8318 |
| 0.2286 | 35.0 | 280 | 0.5313 | 0.7944 |
| 0.2286 | 36.0 | 288 | 0.5189 | 0.8131 |
| 0.2008 | 37.0 | 296 | 0.5590 | 0.7850 |
| 0.1884 | 38.0 | 304 | 0.5488 | 0.7944 |
| 0.1819 | 39.0 | 312 | 0.5563 | 0.8037 |
| 0.1698 | 40.0 | 320 | 0.5679 | 0.7944 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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