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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-base-patch16-224-OT-3
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8709677419354839
---
<!-- 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-base-patch16-224-OT-3
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: 0.3932
- Accuracy: 0.8710
## 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: 4e-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: 0.1
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.91 | 5 | 1.3788 | 0.5 |
| 1.3775 | 2.0 | 11 | 1.3397 | 0.5161 |
| 1.3775 | 2.91 | 16 | 1.2780 | 0.5161 |
| 1.2993 | 4.0 | 22 | 1.1642 | 0.6774 |
| 1.2993 | 4.91 | 27 | 1.0752 | 0.7097 |
| 1.1713 | 6.0 | 33 | 0.9749 | 0.7258 |
| 1.1713 | 6.91 | 38 | 0.8666 | 0.7581 |
| 0.9956 | 8.0 | 44 | 0.7634 | 0.8065 |
| 0.9956 | 8.91 | 49 | 0.6863 | 0.8226 |
| 0.845 | 10.0 | 55 | 0.6005 | 0.8226 |
| 0.7145 | 10.91 | 60 | 0.5364 | 0.8387 |
| 0.7145 | 12.0 | 66 | 0.5585 | 0.8065 |
| 0.5907 | 12.91 | 71 | 0.4962 | 0.7742 |
| 0.5907 | 14.0 | 77 | 0.5070 | 0.7581 |
| 0.5531 | 14.91 | 82 | 0.4648 | 0.8226 |
| 0.5531 | 16.0 | 88 | 0.4812 | 0.7581 |
| 0.4878 | 16.91 | 93 | 0.4281 | 0.8226 |
| 0.4878 | 18.0 | 99 | 0.4796 | 0.7419 |
| 0.4583 | 18.91 | 104 | 0.3913 | 0.8226 |
| 0.4546 | 20.0 | 110 | 0.4085 | 0.7742 |
| 0.4546 | 20.91 | 115 | 0.4016 | 0.8387 |
| 0.4118 | 22.0 | 121 | 0.4125 | 0.8226 |
| 0.4118 | 22.91 | 126 | 0.4282 | 0.8226 |
| 0.3939 | 24.0 | 132 | 0.4869 | 0.7742 |
| 0.3939 | 24.91 | 137 | 0.3723 | 0.8548 |
| 0.4138 | 26.0 | 143 | 0.4032 | 0.8065 |
| 0.4138 | 26.91 | 148 | 0.4397 | 0.8065 |
| 0.3599 | 28.0 | 154 | 0.3714 | 0.8548 |
| 0.3599 | 28.91 | 159 | 0.3800 | 0.8548 |
| 0.3629 | 30.0 | 165 | 0.4158 | 0.8065 |
| 0.336 | 30.91 | 170 | 0.4100 | 0.8226 |
| 0.336 | 32.0 | 176 | 0.4001 | 0.8387 |
| 0.3306 | 32.91 | 181 | 0.3925 | 0.8548 |
| 0.3306 | 34.0 | 187 | 0.3932 | 0.8710 |
| 0.3319 | 34.91 | 192 | 0.3942 | 0.8710 |
| 0.3319 | 36.0 | 198 | 0.3883 | 0.8710 |
| 0.3324 | 36.36 | 200 | 0.3886 | 0.8710 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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