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@@ -42,3 +42,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 20260303_181847/analysis_bundle/cartography/task1_cartography.png filter=lfs diff=lfs merge=lfs -text
 20260305_122917/analysis_bundle/cartography/task1_cartography.csv filter=lfs diff=lfs merge=lfs -text
 20260305_122917/analysis_bundle/cartography/task1_cartography.png filter=lfs diff=lfs merge=lfs -text
+20260305_134923/analysis_bundle/cartography/task1_cartography.csv filter=lfs diff=lfs merge=lfs -text
+20260305_134923/analysis_bundle/cartography/task1_cartography.png filter=lfs diff=lfs merge=lfs -text

20260305_134923/analysis_bundle/cartography/summary.json

@@ -0,0 +1,7 @@
+{
+  "epochs": 3,
+  "task1_rows": 19483,
+  "task1_lowmean_threshold": 0.0,
+  "task1_suspects": 2094,
+  "plot_saved": true
+}

20260305_134923/analysis_bundle/cartography/task1_cartography.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1ef9df1e9e466e552c2e15458d01b719af7101545cefe9d09f0fc6aeabc55051
+size 68922924

20260305_134923/analysis_bundle/metrics/metrics.jsonl

@@ -0,0 +1,3 @@
+{"epoch": 1, "train_loss": 0.31555615859457914, "acc": 0.8879040667361835, "f1": 0.85657104736491, "precision": 0.8273195876288659, "recall": 0.8879668049792531, "score": 0.8879040667361835}
+{"epoch": 2, "train_loss": 0.1605212128245576, "acc": 0.8847758081334723, "f1": 0.85137861466039, "precision": 0.8285340314136126, "recall": 0.8755186721991701, "score": 0.8847758081334723}
+{"epoch": 3, "train_loss": 0.1207108153351422, "acc": 0.8587069864442127, "f1": 0.8252740167633784, "precision": 0.7729468599033816, "recall": 0.8852005532503457, "score": 0.8587069864442127}

20260305_134923/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,2879,0.8614102118791247,0.8236853733981441,0.7945439045183291,0.8550458715596331,0.37860368183397014,0.6213963181660299

20260305_134923/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/20260305_134923,outputs/task1_positive_binary_runs/20260305_134923/best_model.pt,data_for_deberta/dedup_split/positive_test.csv,2879,2879,0.8614102118791247,0.8236853733981441,0.7945439045183291,0.8550458715596331,0.37860368183397014,0.6213963181660299

20260305_134923/analysis_bundle/summaries/summary.json

@@ -0,0 +1,23 @@
+{
+  "best_epoch": 1,
+  "best_score": 0.8879040667361835,
+  "train_rows": 19483,
+  "val_rows": 1918,
+  "final_eval_rows": 2879,
+  "val_metrics": {
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+    "f1": 0.85657104736491,
+    "precision": 0.8273195876288659,
+    "recall": 0.8879668049792531
+  },
+  "final_eval_metrics": {
+    "acc": 0.8614102118791247,
+    "f1": 0.8236853733981441,
+    "precision": 0.7945439045183291,
+    "recall": 0.8550458715596331
+  },
+  "final_eval_baseline": {
+    "always_pick_acc": 0.37860368183397014,
+    "always_decline_acc": 0.6213963181660299
+  }
+}