|
---
|
|
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_fold5
|
|
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: 0.4277190127474912
|
|
---
|
|
|
|
<!-- 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_fold5
|
|
|
|
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: 1.7637
|
|
- Accuracy: 0.4277
|
|
|
|
## 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 |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
|
| 2.3338 | 1.0 | 924 | 2.4489 | 0.2086 |
|
|
| 2.3427 | 2.0 | 1848 | 2.3125 | 0.2517 |
|
|
| 2.1284 | 3.0 | 2772 | 2.2064 | 0.2853 |
|
|
| 2.0324 | 4.0 | 3696 | 2.1236 | 0.3106 |
|
|
| 1.929 | 5.0 | 4620 | 2.0514 | 0.3369 |
|
|
| 1.9691 | 6.0 | 5544 | 1.9984 | 0.3537 |
|
|
| 2.0646 | 7.0 | 6468 | 1.9525 | 0.3653 |
|
|
| 1.8686 | 8.0 | 7392 | 1.9172 | 0.3813 |
|
|
| 1.972 | 9.0 | 8316 | 1.8843 | 0.3916 |
|
|
| 2.0678 | 10.0 | 9240 | 1.8632 | 0.3973 |
|
|
| 1.8342 | 11.0 | 10164 | 1.8414 | 0.3976 |
|
|
| 1.9641 | 12.0 | 11088 | 1.8250 | 0.4057 |
|
|
| 1.6663 | 13.0 | 12012 | 1.8107 | 0.4093 |
|
|
| 1.7839 | 14.0 | 12936 | 1.7966 | 0.4193 |
|
|
| 1.7724 | 15.0 | 13860 | 1.7857 | 0.4258 |
|
|
| 1.7746 | 16.0 | 14784 | 1.7787 | 0.4245 |
|
|
| 1.9266 | 17.0 | 15708 | 1.7714 | 0.4261 |
|
|
| 1.8612 | 18.0 | 16632 | 1.7673 | 0.4280 |
|
|
| 1.7224 | 19.0 | 17556 | 1.7664 | 0.4291 |
|
|
| 1.7078 | 20.0 | 18480 | 1.7637 | 0.4277 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.35.0
|
|
- Pytorch 2.1.0
|
|
- Datasets 2.14.6
|
|
- Tokenizers 0.14.1
|
|
|
