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@@ -58,3 +58,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 20260306_070444/analysis_bundle/cartography/task1_cartography.png filter=lfs diff=lfs merge=lfs -text
 20260306_092824/analysis_bundle/cartography/task1_cartography.csv filter=lfs diff=lfs merge=lfs -text
 20260306_092824/analysis_bundle/cartography/task1_cartography.png filter=lfs diff=lfs merge=lfs -text
+20260306_161747/analysis_bundle/cartography/task1_cartography.csv filter=lfs diff=lfs merge=lfs -text
+20260306_161747/analysis_bundle/cartography/task1_cartography.png filter=lfs diff=lfs merge=lfs -text

20260306_161747/analysis_bundle/cartography/summary.json

@@ -0,0 +1,7 @@
+{
+  "epochs": 3,
+  "task1_rows": 19465,
+  "task1_lowmean_threshold": 0.0,
+  "task1_suspects": 2115,
+  "plot_saved": true
+}

20260306_161747/analysis_bundle/cartography/task1_cartography.csv

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+oid sha256:f47fbe27bd257513815f8108225ec5b903c96060d5985ad84e022fb660af0d2c
+size 68840506

20260306_161747/analysis_bundle/metrics/metrics.jsonl

@@ -0,0 +1,3 @@
+{"epoch": 1, "train_loss": 0.2988610934640603, "acc": 0.8806047966631908, "f1": 0.8390723822909346, "precision": 0.8361344537815126, "recall": 0.842031029619182, "score": 0.8806047966631908}
+{"epoch": 2, "train_loss": 0.14993673105377492, "acc": 0.8733055265901981, "f1": 0.8270462633451957, "precision": 0.8347701149425287, "recall": 0.8194640338504936, "score": 0.8733055265901981}
+{"epoch": 3, "train_loss": 0.11598749612760328, "acc": 0.8607924921793535, "f1": 0.8086021505376344, "precision": 0.8221574344023324, "recall": 0.7954866008462623, "score": 0.8607924921793535}

20260306_161747/analysis_bundle/summaries/final_eval_summary.csv

@@ -0,0 +1,2 @@
+dataset,rows_evaluated,acc,f1,precision,recall,always_pick_acc,always_decline_acc
+data_for_deberta/dedup_split/positive_test.csv,2879,0.8753039249739493,0.8365953573054165,0.825696316262354,0.8477859778597786,0.37651962486974644,0.6234803751302536

20260306_161747/analysis_bundle/summaries/final_eval_summary_evalonly.csv

@@ -0,0 +1,2 @@
+run_dir,model_path,dataset,rows_raw,rows_evaluated,acc,f1,precision,recall,always_pick_acc,always_decline_acc
+outputs/task1_positive_binary_runs/20260306_161747,outputs/task1_positive_binary_runs/20260306_161747/best_model.pt,data_for_deberta/dedup_split/positive_test.csv,2879,2879,0.8753039249739493,0.8365953573054165,0.825696316262354,0.8477859778597786,0.37651962486974644,0.6234803751302536

20260306_161747/analysis_bundle/summaries/summary.json

@@ -0,0 +1,23 @@
+{
+  "best_epoch": 1,
+  "best_score": 0.8806047966631908,
+  "train_rows": 19465,
+  "val_rows": 1918,
+  "final_eval_rows": 2879,
+  "val_metrics": {
+    "acc": 0.8806047966631908,
+    "f1": 0.8390723822909346,
+    "precision": 0.8361344537815126,
+    "recall": 0.842031029619182
+  },
+  "final_eval_metrics": {
+    "acc": 0.8753039249739493,
+    "f1": 0.8365953573054165,
+    "precision": 0.825696316262354,
+    "recall": 0.8477859778597786
+  },
+  "final_eval_baseline": {
+    "always_pick_acc": 0.37651962486974644,
+    "always_decline_acc": 0.6234803751302536
+  }
+}