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Sonja Topf
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changed seed and readme
Browse files- README.md +1 -2
- checkpoints/model.pt +1 -1
- config/config.json +1 -1
README.md
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@@ -13,7 +13,7 @@ short_description: Graph Isomorphism Network Baseline Classifier for Tox21
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This repository hosts a Hugging Face Space that provides an examplary API for submitting models to the [Tox21 Leaderboard](https://huggingface.co/spaces/tschouis/tox21_leaderboard).
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In this example, we trained a GIN classifier on the Tox21 targets and saved the trained model in the `
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**Important:** For leaderboard submission, your Space needs to include training code. The file `train.py` should train the model using the config specified inside the `config/` folder and save the final model parameters into a file inside the `checkpoints/` folder. The model should be trained using the [Tox21_dataset](https://huggingface.co/datasets/tschouis/tox21) provided on Hugging Face. The datasets can be loaded like this:
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```python
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- `app.py` - FastAPI application wrapper (can be used as-is).
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- `train.py` - trains and saves a model using the config in the `config/` folder.
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- `config/` - the config file used by `train.py`.
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- `logs/` - all the logs of `train.py`, the saved model, and predictions on the validation set.
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- `checkpoints/` - the saved model that is used in `predict.py` is here.
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- `src/` - Core model & preprocessing logic:
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This repository hosts a Hugging Face Space that provides an examplary API for submitting models to the [Tox21 Leaderboard](https://huggingface.co/spaces/tschouis/tox21_leaderboard).
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In this example, we trained a GIN classifier on the Tox21 targets and saved the trained model in the `checkpoints/` folder.
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**Important:** For leaderboard submission, your Space needs to include training code. The file `train.py` should train the model using the config specified inside the `config/` folder and save the final model parameters into a file inside the `checkpoints/` folder. The model should be trained using the [Tox21_dataset](https://huggingface.co/datasets/tschouis/tox21) provided on Hugging Face. The datasets can be loaded like this:
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```python
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- `app.py` - FastAPI application wrapper (can be used as-is).
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- `train.py` - trains and saves a model using the config in the `config/` folder.
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- `config/` - the config file used by `train.py`.
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- `checkpoints/` - the saved model that is used in `predict.py` is here.
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- `src/` - Core model & preprocessing logic:
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checkpoints/model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 628746
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version https://git-lfs.github.com/spec/v1
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oid sha256:2e3b2354e9323de072794b7bc4603fee711931b8f9fbbd4e49aab691253bd748
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size 628746
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config/config.json
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"patience": 100,
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"max_epochs": 200,
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"batch_size": 64,
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"seed":
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"add_or_mean": "mean",
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"window_size": 15
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}
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"patience": 100,
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"max_epochs": 200,
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"batch_size": 64,
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"seed": 42,
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"add_or_mean": "mean",
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"window_size": 15
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}
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