Upload train.py with huggingface_hub

train.py

@@ -8,105 +8,12 @@ from span_marker.model_card import SpanMarkerModelCardData
 from huggingface_hub import upload_folder, upload_file
 
 
-"""
-FEATURES = Features({"tokens": Sequence(feature=Value(dtype='string')), "ner_tags": Sequence(feature=ClassLabel(names=['O', 'B-ORG', 'I-ORG']))})
-
-
-def load_fewnerd():
-    def mapper(sample):
-        sample["ner_tags"] = [int(tag == 5) for tag in sample["ner_tags"]]
-        sample["ner_tags"] = [2 if tag == 1 and idx > 0 and sample["ner_tags"][idx - 1] == 1 else tag for idx, tag in enumerate(sample["ner_tags"])]
-        return sample
-    
-    dataset = load_dataset("DFKI-SLT/few-nerd", "supervised")
-    dataset = dataset.map(mapper, remove_columns=["id", "fine_ner_tags"])
-    dataset = dataset.cast(FEATURES)
-    return dataset
-
-
-def load_conll():
-    label_mapping = {3: 1, 4: 2}
-    def mapper(sample):
-        sample["ner_tags"] = [label_mapping.get(tag, 0) for tag in sample["ner_tags"]]
-        return sample
-
-    dataset = load_dataset("conll2003")
-    dataset = dataset.map(mapper, remove_columns=["id", "pos_tags", "chunk_tags"])
-    dataset = dataset.cast(FEATURES)
-    return dataset
-
-
-def load_ontonotes():
-    label_mapping = {11: 1, 12: 2}
-    def mapper(sample):
-        sample["ner_tags"] = [label_mapping.get(tag, 0) for tag in sample["ner_tags"]]
-        return sample
-
-    dataset = load_dataset("tner/ontonotes5")
-    dataset = dataset.rename_column("tags", "ner_tags")
-    dataset = dataset.map(mapper)
-    dataset = dataset.cast(FEATURES)
-    return dataset
-
-
-def load_multinerd():
-    label_mapping = {5: 1, 6: 2}
-    def mapper(sample):
-        sample["ner_tags"] = [label_mapping.get(tag, 0) for tag in sample["ner_tags"]]
-        return sample
-
-    def lang_filter(sample):
-        return sample["lang"] == "en"
-
-    dataset = load_dataset("Babelscape/multinerd")
-    dataset = dataset.filter(lang_filter)
-    dataset = dataset.map(mapper, remove_columns="lang")
-    dataset = dataset.cast(FEATURES)
-    return dataset
-
-
-def preprocess_raw_dataset(raw_dataset):
-    # Set the number of sentences without an org equal to the number of sentences with an org
-    def has_org(sample):
-        return bool(sum(sample["ner_tags"]))
-    
-    def has_no_org(sample):
-        return not has_org(sample)
-
-    dataset_org = raw_dataset.filter(has_org)
-    dataset_no_org = raw_dataset.filter(has_no_org)
-    dataset_no_org = dataset_no_org.select(random.sample(range(len(dataset_no_org)), k=len(dataset_org)))
-    dataset = concatenate_datasets([dataset_org, dataset_no_org])
-    return dataset
-"""
-
 
 def main() -> None:
     # Load the dataset, ensure "tokens" and "ner_tags" columns, and get a list of labels
     labels = ["O", "B-ORG", "I-ORG"]
-    """
-    fewnerd_dataset = load_fewnerd()
-    conll_dataset = load_conll()
-    ontonotes_dataset = load_ontonotes()
-    multinerd_dataset = load_multinerd()
-
-    raw_train_dataset = concatenate_datasets([fewnerd_dataset["train"], conll_dataset["train"], ontonotes_dataset["train"], multinerd_dataset["train"]])
-    raw_eval_dataset = concatenate_datasets([fewnerd_dataset["validation"], conll_dataset["validation"], ontonotes_dataset["validation"], multinerd_dataset["validation"]])
-    raw_test_dataset = concatenate_datasets([fewnerd_dataset["test"], conll_dataset["test"], ontonotes_dataset["test"], multinerd_dataset["test"]])
-
-    train_dataset = preprocess_raw_dataset(raw_train_dataset)
-    eval_dataset = preprocess_raw_dataset(raw_eval_dataset)
-    test_dataset = preprocess_raw_dataset(raw_test_dataset)
-
-    dataset_dict = DatasetDict({
-        "train": train_dataset,
-        "validation": eval_dataset,
-        "test": test_dataset,
-    })
-    dataset_dict.push_to_hub("ner-orgs", private=True)
-    """
-    # breakpoint()
-    dataset = load_dataset("tomaarsen/ner-orgs")
+    dataset_id = "tomaarsen/ner-orgs"
+    dataset = load_dataset(dataset_id)
 
     train_dataset = dataset["train"]
     eval_dataset = dataset["validation"]
@@ -126,8 +33,10 @@ def main() -> None:
         # Model card variables
         model_card_data=SpanMarkerModelCardData(
             model_id=model_id,
+            dataset_id=dataset_id,
             encoder_id=encoder_id,
-            dataset_name="FewNERD, CoNLL2003, OntoNotes v5, and MultiNERD",
+            dataset_name="FewNERD, CoNLL2003, and OntoNotes v5",
+            license="cc-by-sa-4.0",
             language=["en"],
         ),
     )