https://github.com/luocfprime/dtd_experiment
https://github.com/luocfprime/dtd_experiment
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/luocfprime/dtd_experiment
- Owner: luocfprime
- Created: 2023-11-03T16:36:44.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-11-05T03:41:57.000Z (about 2 years ago)
- Last Synced: 2025-09-26T15:49:47.047Z (4 months ago)
- Language: Python
- Size: 40.5 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Experiment on DTD Dataset
## Experiment Setting
| config | use pretrained | freeze backbone | freeze until epoch | gradient clip | augmentation | use scheduler |
|:------:|:--------------:|:---------------:|:------------------:|:-------------:|:------------:|:-------------:|
| exp1 | √ | √ | 15 | √ | √ | √ |
| exp2 | √ | √ | 15 | √ | x | √ |
| exp3 | √ | √ | 15 | √ | √ | x |
| exp4 | √ | √ | 15 | x | √ | √ |
| exp5 | √ | √ | - | √ | √ | √ |
| exp6 | √ | x | - | √ | √ | √ |
| exp7 | x | - | - | √ | √ | √ |
| exp8 | x | - | - | x | √ | √ |
| exp9 | x | - | - | x | x | √ |
| exp10 | x | - | - | x | x | x |
> **freeze until epoch:** freeze backbone until this epoch, then unfreeze
> **gradient clip:** clip gradient norm to 10
> **augmentation:** random rotation, random horizontal flip, color jitter
- exp1: full
- exp2: w/o augmentation
- exp3: w/o scheduler
- exp4: w/o gradient clip
- exp5: w/o unfreeze (keep backbone frozen during entire training)
- exp6: w/o freeze backbone
- exp7: w/o pretrained
- exp8: w/o pretrained, w/o gradient clip
- exp9: w/o pretrained, w/o gradient clip, w/o augmentation
- exp10: w/o pretrained, w/o gradient clip, w/o augmentation, w/o scheduler
**Other hyperparameters settings:**
- batch size: 64
- optimizer: SGD
- learning rate: 0.01
- momentum: 0.9
- weight decay: 0.0001
- scheduler: StepLR (if used)
- lr_scheduler_step_size: 10
- lr_scheduler_gamma: 0.1
## Experiment Result
See the full wandb log [here](https://wandb.ai/lcf235/ResNet18_DTD_full_experiment).
## To Reproduce
Go to the root directory of this project, then run the following command to reproduce full experiment:
```bash
ls -l config | awk '{print $9}' | grep .yml | xargs -n 1 -I {} python train.py config/{}
```