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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
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: 0.8225806451612904
---
<!-- 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
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: 0.4801
- Accuracy: 0.8226
## 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: 0.1
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.89 | 4 | 1.7603 | 0.1452 |
| No log | 2.0 | 9 | 1.6852 | 0.1452 |
| 1.7571 | 2.89 | 13 | 1.5655 | 0.1452 |
| 1.7571 | 4.0 | 18 | 1.3816 | 0.1452 |
| 1.5255 | 4.89 | 22 | 1.2599 | 0.3226 |
| 1.5255 | 6.0 | 27 | 1.1534 | 0.4839 |
| 1.2245 | 6.89 | 31 | 1.0641 | 0.4839 |
| 1.2245 | 8.0 | 36 | 1.0372 | 0.4355 |
| 1.0438 | 8.89 | 40 | 0.9988 | 0.4355 |
| 1.0438 | 10.0 | 45 | 0.9260 | 0.5161 |
| 1.0438 | 10.89 | 49 | 0.9085 | 0.7097 |
| 0.9727 | 12.0 | 54 | 0.8433 | 0.7258 |
| 0.9727 | 12.89 | 58 | 0.7529 | 0.7742 |
| 0.8469 | 14.0 | 63 | 0.7187 | 0.7581 |
| 0.8469 | 14.89 | 67 | 0.6806 | 0.7258 |
| 0.6908 | 16.0 | 72 | 0.6576 | 0.7581 |
| 0.6908 | 16.89 | 76 | 0.5742 | 0.7903 |
| 0.6064 | 18.0 | 81 | 0.6447 | 0.7581 |
| 0.6064 | 18.89 | 85 | 0.5602 | 0.7742 |
| 0.5303 | 20.0 | 90 | 0.4943 | 0.7903 |
| 0.5303 | 20.89 | 94 | 0.5304 | 0.7903 |
| 0.5303 | 22.0 | 99 | 0.4801 | 0.8226 |
| 0.4903 | 22.89 | 103 | 0.4849 | 0.8226 |
| 0.4903 | 24.0 | 108 | 0.5710 | 0.7742 |
| 0.4261 | 24.89 | 112 | 0.4803 | 0.7903 |
| 0.4261 | 26.0 | 117 | 0.5671 | 0.7258 |
| 0.4122 | 26.89 | 121 | 0.4585 | 0.8065 |
| 0.4122 | 28.0 | 126 | 0.5910 | 0.7097 |
| 0.3739 | 28.89 | 130 | 0.5821 | 0.7581 |
| 0.3739 | 30.0 | 135 | 0.5329 | 0.7742 |
| 0.3739 | 30.89 | 139 | 0.4423 | 0.8226 |
| 0.3896 | 32.0 | 144 | 0.4716 | 0.7581 |
| 0.3896 | 32.89 | 148 | 0.4786 | 0.7903 |
| 0.3472 | 34.0 | 153 | 0.4538 | 0.7903 |
| 0.3472 | 34.89 | 157 | 0.4553 | 0.7903 |
| 0.3349 | 35.56 | 160 | 0.4528 | 0.7903 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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