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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_fold1
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: 0.4165082812924247
---
<!-- 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_fold1
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: 1.8239
- Accuracy: 0.4165
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.5085 | 1.0 | 924 | 2.4731 | 0.1963 |
| 2.3692 | 2.0 | 1848 | 2.3352 | 0.2465 |
| 2.3278 | 3.0 | 2772 | 2.2372 | 0.2780 |
| 2.1219 | 4.0 | 3696 | 2.1632 | 0.3044 |
| 2.2732 | 5.0 | 4620 | 2.1014 | 0.3342 |
| 2.0973 | 6.0 | 5544 | 2.0509 | 0.3511 |
| 2.0974 | 7.0 | 6468 | 2.0095 | 0.3633 |
| 2.0888 | 8.0 | 7392 | 1.9760 | 0.3698 |
| 1.9477 | 9.0 | 8316 | 1.9428 | 0.3842 |
| 1.937 | 10.0 | 9240 | 1.9178 | 0.3932 |
| 1.9658 | 11.0 | 10164 | 1.8968 | 0.3932 |
| 1.9052 | 12.0 | 11088 | 1.8809 | 0.3975 |
| 1.7933 | 13.0 | 12012 | 1.8676 | 0.4032 |
| 1.9046 | 14.0 | 12936 | 1.8552 | 0.4062 |
| 1.8301 | 15.0 | 13860 | 1.8450 | 0.4075 |
| 1.8479 | 16.0 | 14784 | 1.8378 | 0.4122 |
| 1.8401 | 17.0 | 15708 | 1.8313 | 0.4138 |
| 1.7985 | 18.0 | 16632 | 1.8281 | 0.4154 |
| 1.8691 | 19.0 | 17556 | 1.8245 | 0.4181 |
| 1.8762 | 20.0 | 18480 | 1.8239 | 0.4165 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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