Comments (3)
1st one is to add them to the registry so that they can be instantiated using their registered name e.g. through the config files just like the remaining parts (model, tokenizer etc) of a training experiment.
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As currently WIP in obss/jury#48, I soon implement metrics extending datasets.Metric, so we can definitely support this seamlessly through jury without datasets,
- I'm not sure what we may want here, is this to enable users to write custom metrics ?
- Will finish jury task first, then it would be very easy to implement this here.
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Already merged.
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Related Issues (20)
- Fix _create_compute_metrics method in TransformerTrainer HOT 1
- Use dataset.set_format in dataset collator
- Refactor tests HOT 1
- Improve fixture dataset caching and removal HOT 1
- Implement CONLL2003 POS tagging as an example for trapper
- Support global plugin files as well
- Train a POS tagging model
- Refactor pipelines HOT 1
- Fix setup.py by limiting the released packages
- black is not formatting several directories
- Add ignored_labels attribute to the LabelMapper class
- Update transformers and allennlp dependencies to receive the fix on question answering pipeline
- Add Seq2SeqTrainer support from transformers
- Investigate relaxing seqeval and tensorboardX requirements.
- transformers' callback integration
- Correct in `_chop_excess_context_tokens` method in `SquadDataProcessor` HOT 1
- Remove `overrides` decorator from the `Run` command
- Add Tests for Commands
- POS Tagging Example Not Working
- _run_experiment_from_params crashes during distributed training due to directory creation multiple times
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