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---
license: apache-2.0
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: pedestrian_age_recognition_local
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: 0.8073394495412844
---
<!-- 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. -->
# pedestrian_age_recognition_local
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: 0.5004
- Accuracy: 0.8073
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8849 | 1.0 | 2008 | 0.7939 | 0.6807 |
| 0.9836 | 2.0 | 4016 | 0.6694 | 0.7336 |
| 0.8128 | 3.0 | 6024 | 0.5768 | 0.7668 |
| 0.7611 | 4.0 | 8032 | 0.5541 | 0.7833 |
| 0.6441 | 5.0 | 10040 | 0.5473 | 0.7773 |
| 0.5696 | 6.0 | 12048 | 0.5187 | 0.7971 |
| 0.6925 | 7.0 | 14056 | 0.5082 | 0.8038 |
| 0.5711 | 8.0 | 16064 | 0.5092 | 0.8098 |
| 0.7741 | 9.0 | 18072 | 0.5026 | 0.8020 |
| 0.5269 | 10.0 | 20080 | 0.5004 | 0.8073 |
### Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
### Contact information
For personal communication related to this project, please contact Nha Nguyen Van (nha282@gmail.com). |