|
---
|
|
license: apache-2.0
|
|
base_model: facebook/deit-tiny-patch16-224
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- imagefolder
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: Boya1_Adamax_1-e4_20Epoch_Deit-tiny-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: 0.5568829758349172
|
|
---
|
|
|
|
<!-- 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_Adamax_1-e4_20Epoch_Deit-tiny-patch16_fold1
|
|
|
|
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 3.5356
|
|
- Accuracy: 0.5569
|
|
|
|
## 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: 0.0001
|
|
- 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 |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
|
| 1.3865 | 1.0 | 924 | 1.5601 | 0.4768 |
|
|
| 1.2182 | 2.0 | 1848 | 1.4517 | 0.4963 |
|
|
| 1.2424 | 3.0 | 2772 | 1.3040 | 0.5531 |
|
|
| 0.8291 | 4.0 | 3696 | 1.3092 | 0.5745 |
|
|
| 0.6764 | 5.0 | 4620 | 1.3977 | 0.5724 |
|
|
| 0.5779 | 6.0 | 5544 | 1.5087 | 0.5601 |
|
|
| 0.3166 | 7.0 | 6468 | 1.7036 | 0.5577 |
|
|
| 0.2404 | 8.0 | 7392 | 1.9068 | 0.5528 |
|
|
| 0.144 | 9.0 | 8316 | 2.1442 | 0.5547 |
|
|
| 0.165 | 10.0 | 9240 | 2.4839 | 0.5509 |
|
|
| 0.0646 | 11.0 | 10164 | 2.7042 | 0.5490 |
|
|
| 0.0029 | 12.0 | 11088 | 2.9034 | 0.5523 |
|
|
| 0.0317 | 13.0 | 12012 | 3.1091 | 0.5504 |
|
|
| 0.0012 | 14.0 | 12936 | 3.2476 | 0.5496 |
|
|
| 0.0008 | 15.0 | 13860 | 3.3162 | 0.5569 |
|
|
| 0.0005 | 16.0 | 14784 | 3.3879 | 0.5525 |
|
|
| 0.0003 | 17.0 | 15708 | 3.4370 | 0.5517 |
|
|
| 0.0007 | 18.0 | 16632 | 3.4907 | 0.5542 |
|
|
| 0.0003 | 19.0 | 17556 | 3.5171 | 0.5566 |
|
|
| 0.0003 | 20.0 | 18480 | 3.5356 | 0.5569 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.40.1
|
|
- Pytorch 2.1.0
|
|
- Datasets 2.19.0
|
|
- Tokenizers 0.19.1
|
|
|
