chore(defaults): set BioBERT v1.1 + conll2003 and epochs=3 as baseline

app.py

@@ -8,8 +8,8 @@ import gradio as gr
 from huggingface_hub import HfApi, create_repo, hf_hub_url
 
 
-DEFAULT_BASE_MODEL = "dmis-lab/biobert-base-cased-v1.2"
-DEFAULT_DATASET = "wikiann:en"  # robust default; medical sets may require custom preprocessing
+DEFAULT_BASE_MODEL = "dmis-lab/biobert-base-cased-v1.1"
+DEFAULT_DATASET = "conll2003"  # stronger baseline default
 TARGET_REPO = os.getenv("MEDVLLM_TARGET_REPO", "Junaidi-AI/med-vllm")
 
 
@@ -368,7 +368,7 @@ def build_ui():
                 label="Dataset (token classification)",
             )
         with gr.Row():
-            epochs = gr.Slider(minimum=1, maximum=3, step=1, value=1, label="Epochs")
+            epochs = gr.Slider(minimum=1, maximum=5, step=1, value=3, label="Epochs")
             batch = gr.Slider(minimum=4, maximum=16, step=2, value=8, label="Batch size")
             lr = gr.Textbox(value="2e-5", label="Learning rate")
         with gr.Row():