Commit 068fde83 authored by Fabian Ziegner's avatar Fabian Ziegner
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parent 34bc457f
......@@ -3,7 +3,27 @@ Workflow
1. Install required packages
2. Make sure a MongoDB instance is set up and runnning
3. Fill in your database credentials in .mongo.conf
3. Fill in your database credentials in .mongo.conf (see
4. Fill in your desired settings in config.yaml
5. Run to start the experiment(s)
6. Run to get a dataframe containing experiment results
- name: Name of the experiment
- user: Username of the database
- host: Address of the database
- port: Port of the database
- database: Name of the database
- auth: Name of the authentication database
- pw: Password of the database
- device: GPU to use (see nvidia-smi for device numbers)
- batch_size: Batch size
- representation: A huggingface model (see
- multi_threshold: Score threshold to use (see mlmc.thresholds.thresholds_dict.keys()). Single-label datasets will always use max prediction.
- formatted: If formatting is set to True each class label is replaced by a more descriptive label. Furthermore, if the huggingface method is used the hypothesis is replaced as well.
- cut_sample: Trims the input text to the maximum input size of the language model.
- method: "huggingface" or "flair"
- whole_dataset: If True the entire dataset is used for classification.
- datasets: Datasets to use (see
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