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  • Qbiwan's avatar
    Update run_xnli.py to use Datasets library (#9829) · 8dcfaea0
    Qbiwan authored 
    * remove xnli_compute_metrics, add load_dataset, load_metric, set_seed,metric.compute,load_metric

* fix

* fix

* fix

* push

* fix

* everything works

* fix init

* fix

* special treatment for sepconv1d

* style

* 馃檹馃徑

* add doc and cleanup


* fix doc

* fix doc again

* fix doc again

* Apply suggestions from code review

* make style

* Proposal that should work

* Remove needless code

* Fix test

* Apply suggestions from code review

* remove xnli_compute_metrics, add load_dataset, load_metric, set_seed,metric.compute,load_metric

* amend README

* removed data_args.task_name and replaced with task_name = "xnli"; use split function to load train and validation dataset separately; remove __post_init__; remove flag --task_name from README.

* removed dict task_to_keys, use str "xnli" instead of variable task_name, change preprocess_function to use examples["premise"], examples["hypothesis"] directly, remove sentence1_key and sentence2_key, change compute_metrics function to cater only to accuracy metric, add condition for train_langauge is None when using dataset.load_dataset()

* removed `torch.distributed.barrier()` and `import torch` as `from_pretrained` is able to do the work; amend README
    8dcfaea0
run_xnli.py 12.7 KB