Upload train_ner_pii.py with huggingface_hub

train_ner_pii.py

@@ -124,18 +124,17 @@ label2id = {l: i for i, l in id2label.items()}
 
 # ── Config ────────────────────────────────────────────────────────────────────
 MODEL_NAME   = "answerdotai/ModernBERT-base"        # train from base
-DATASET_NAME = "ai4privacy/pii-masking-200k"
-HUB_MODEL_ID = "jefftherover/modernbert-pii-mapped-v3"
-OUTPUT_DIR   = "modernbert-pii-mapped-v3"
+DATASET_NAME = "jefftherover/pii-masking-200k-DOBfixed"
+HUB_MODEL_ID = "jefftherover/modernbert-pii-mapped-v4"
+OUTPUT_DIR   = "modernbert-pii-mapped-v4"
 MAX_LENGTH   = 512
 
 print(f"Labels ({len(label_list)}): {label_list}")
 
 # ── Dataset ───────────────────────────────────────────────────────────────────
 print("Loading dataset...")
-full = load_dataset(DATASET_NAME, split="train")
-en   = full.filter(lambda x: x["language"] == "en")
-print(f"English rows: {len(en)}")
+en = load_dataset(DATASET_NAME, split="train")
+print(f"Rows: {len(en)}")
 
 splits   = en.train_test_split(test_size=0.1, seed=42)
 train_ds = splits["train"]
@@ -235,7 +234,7 @@ model = AutoModelForTokenClassification.from_pretrained(
 )
 
 # ── Trackio ───────────────────────────────────────────────────────────────────
-trackio.init(project="modernbert-pii-mapped", name="modernbert-pii-mapped-v3")
+trackio.init(project="modernbert-pii-mapped", name="modernbert-pii-mapped-v4")
 
 # ── Training args ─────────────────────────────────────────────────────────────
 args = TrainingArguments(
@@ -261,7 +260,7 @@ args = TrainingArguments(
     hub_private_repo=False,
     hub_strategy="every_save",
     report_to="trackio",
-    run_name="modernbert-pii-mapped-v3",
+    run_name="modernbert-pii-mapped-v4",
     fp16=True,
     logging_steps=100,
     dataloader_num_workers=2,