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license: mit
tags:
- fashion-mnist
- image-classification
---
# CO3133 course project checkpoints, group DeepDive
Selected runs for the three course assignments. Weights are never committed to git; this
repository is the only place they live.
```
<assignment>/runs/<run_id>/
checkpoint.pt weights, selected by the checkpoint rule in config.yaml
config.yaml the resolved configuration that produced them
environment.json commit hash, library versions, hardware, thread count
history.json one record per epoch
summary.json parameters, best epoch, training time, selected metric
checksums.json SHA-256 of every file above
```
## Reconstructing a checkpoint
Clone [the repository](https://github.com/longlephamtien/DL261-Assignment) at the commit
recorded in `environment.json`, then run the model configuration named in `config.yaml` with
the seed it records:
```sh
cd assignments
python -m venv .venv && source .venv/bin/activate
pip install -e .
cd assignment-1
python -m src.data --config configs/base.yaml
python -m src.train --config configs/<model>.yaml --set seed=<seed>
```
The dataset split is fixed and committed, so the run reproduces the reported accuracy and
macro-F1 on any machine. Wall-clock times depend on the hardware recorded in
`environment.json`.
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