deit_flyswot / README.md
---
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- f1
model-index:
- name: deit_flyswot
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
metrics:
- name: F1
type: f1
value: 0.990761405263678
---
<!-- 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. -->
# deit_flyswot
This model was trained from scratch on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0755
- F1: 0.9908
## 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: 32
- eval_batch_size: 32
- seed: 666
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 52 | 0.5710 | 0.8095 |
| No log | 2.0 | 104 | 0.2814 | 0.9380 |
| No log | 3.0 | 156 | 0.1719 | 0.9555 |
| No log | 4.0 | 208 | 0.1410 | 0.9692 |
| No log | 5.0 | 260 | 0.1457 | 0.9680 |
| No log | 6.0 | 312 | 0.1084 | 0.9747 |
| No log | 7.0 | 364 | 0.0892 | 0.9736 |
| No log | 8.0 | 416 | 0.0962 | 0.9831 |
| No log | 9.0 | 468 | 0.0819 | 0.9796 |
| 0.2034 | 10.0 | 520 | 0.0916 | 0.9778 |
| 0.2034 | 11.0 | 572 | 0.0793 | 0.9827 |
| 0.2034 | 12.0 | 624 | 0.0818 | 0.9894 |
| 0.2034 | 13.0 | 676 | 0.0852 | 0.9807 |
| 0.2034 | 14.0 | 728 | 0.0938 | 0.9778 |
| 0.2034 | 15.0 | 780 | 0.0814 | 0.9876 |
| 0.2034 | 16.0 | 832 | 0.0702 | 0.9892 |
| 0.2034 | 17.0 | 884 | 0.0801 | 0.9892 |
| 0.2034 | 18.0 | 936 | 0.0806 | 0.9892 |
| 0.2034 | 19.0 | 988 | 0.0769 | 0.9926 |
| 0.0115 | 20.0 | 1040 | 0.0800 | 0.9926 |
| 0.0115 | 21.0 | 1092 | 0.0794 | 0.9926 |
| 0.0115 | 22.0 | 1144 | 0.0762 | 0.9846 |
| 0.0115 | 23.0 | 1196 | 0.0789 | 0.9830 |
| 0.0115 | 24.0 | 1248 | 0.0794 | 0.9829 |
| 0.0115 | 25.0 | 1300 | 0.0770 | 0.9908 |
| 0.0115 | 26.0 | 1352 | 0.0791 | 0.9829 |
| 0.0115 | 27.0 | 1404 | 0.0813 | 0.9892 |
| 0.0115 | 28.0 | 1456 | 0.0816 | 0.9908 |
| 0.0058 | 29.0 | 1508 | 0.0774 | 0.9908 |
| 0.0058 | 30.0 | 1560 | 0.0755 | 0.9908 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6