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---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_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: 0.41702702702702704
---
<!-- 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. -->
# Boya1_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold2
This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8092
- Accuracy: 0.4170
## 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: 16
- eval_batch_size: 16
- 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.364 | 1.0 | 923 | 2.4299 | 0.2108 |
| 2.3719 | 2.0 | 1846 | 2.2817 | 0.2649 |
| 2.2408 | 3.0 | 2769 | 2.1860 | 0.2889 |
| 2.1829 | 4.0 | 3692 | 2.1102 | 0.3143 |
| 2.0369 | 5.0 | 4615 | 2.0577 | 0.3241 |
| 2.061 | 6.0 | 5538 | 2.0066 | 0.3419 |
| 1.9167 | 7.0 | 6461 | 1.9797 | 0.3568 |
| 2.0057 | 8.0 | 7384 | 1.9411 | 0.3673 |
| 2.0098 | 9.0 | 8307 | 1.9258 | 0.3722 |
| 1.9046 | 10.0 | 9230 | 1.9019 | 0.3822 |
| 1.862 | 11.0 | 10153 | 1.8785 | 0.3922 |
| 1.8051 | 12.0 | 11076 | 1.8624 | 0.3973 |
| 1.8752 | 13.0 | 11999 | 1.8478 | 0.3981 |
| 1.9831 | 14.0 | 12922 | 1.8389 | 0.4032 |
| 1.8913 | 15.0 | 13845 | 1.8338 | 0.4051 |
| 1.9373 | 16.0 | 14768 | 1.8269 | 0.4086 |
| 1.8457 | 17.0 | 15691 | 1.8202 | 0.4089 |
| 1.7936 | 18.0 | 16614 | 1.8117 | 0.4159 |
| 1.7608 | 19.0 | 17537 | 1.8101 | 0.4168 |
| 1.9672 | 20.0 | 18460 | 1.8092 | 0.4170 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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