changed the finetune task for full test as well

app.py

@@ -37,7 +37,7 @@ def process_file(model_name,inc_slider,progress=Progress(track_tqdm=True)):
     elif(model_name=="ASTRA-FT-FULL"):
         # test_info_location=parent_location+"fullTest/test_info.txt"
         # test_location=parent_location+"fullTest/test.txt"
-        finetune_task="highGRschool10"
+        finetune_task="fullTest"
     else:
         finetune_task=None
     # Load the test_info file and the graduation rate file
@@ -153,6 +153,7 @@ def process_file(model_name,inc_slider,progress=Progress(track_tqdm=True)):
 
 
     progress(0.2, desc="analysis done!! Executing models")
+    print("finetuned task: ",finetune_task)
     subprocess.run([
         "python", "new_test_saved_finetuned_model.py",
         "-workspace_name", "ratio_proportion_change3_2223/sch_largest_100-coded",
@@ -208,7 +209,8 @@ def process_file(model_name,inc_slider,progress=Progress(track_tqdm=True)):
 
 # List of models for the dropdown menu
 
-models = ["ASTRA-FT-HGR", "ASTRA-FT-LGR", "ASTRA-FT-FULL"]
+# models = ["ASTRA-FT-HGR", "ASTRA-FT-LGR", "ASTRA-FT-FULL"]
+models = ["ASTRA-FT-HGR", "ASTRA-FT-FULL"]
 content = """
 <h1 style="color: white;">ASTRA: An AI Model for Analyzing Math Strategies</h1>
 
@@ -238,7 +240,6 @@ lead to correct vs. incorrect solutions.</p>
     <li style="color: white;">Select a fine-tuned model:
         <ul style="color: white;">
             <li style="color: white;">ASTRA-FT-HGR: Fine-tuned with a small sample of data from schools that have a high graduation rate.</li>
-            <li style="color: white;">ASTRA-FT-LGR: Fine-tuned with a small sample of data from schools that have a low graduation rate.</li>
             <li style="color: white;">ASTRA-FT-Full: Fine-tuned with a small sample of data from a mix of schools that have high/low graduation rates.</li>
         </ul>
     </li>

ratio_proportion_change3_2223/sch_largest_100-coded/finetuning/fullTest/test.txt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2a479561b801a43249b6a8aceed5f32d16cec3d2f40956ed02640b6dcab0bdfe
-size 21353853
+oid sha256:35569d6f81ef85e6353f36912c1cb79bfb723fe7d2476e10afcb745c170c5130
+size 24672844

ratio_proportion_change3_2223/sch_largest_100-coded/finetuning/fullTest/test_info.txt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:dbb182b48eecce59c4e61f82a23d8af2866d9327f0543aca3546880fdb0d6003
-size 166442240
+oid sha256:a6aadba0002bfdfde835b8837b3ff36cd84c64c3e23b6589ec1d002b4b62c2f4
+size 122629427

result.txt

@@ -1,7 +1,7 @@
-avg_loss: 0.5820454359054565
-total_acc: 69.02834008097166
-precisions: 0.7233000757179396
-recalls: 0.6902834008097166
-f1_scores: 0.680564448931978
-time_taken_from_start: 33.72925329208374
-auc_score: 0.7527458335895701
+avg_loss: 0.5841353535652161
+total_acc: 69.00702106318957
+precisions: 0.7236623191454734
+recalls: 0.6900702106318957
+f1_scores: 0.6802420656474512
+time_taken_from_start: 30.22950553894043
+auc_score: 0.7457100293916334

roc_data.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:57ef1d1fe518f78a1087a3605e61462c3489cfbd0e2b7cc7bc9cf4b6360b60f7
-size 9917
+oid sha256:1eec496eaf0223a6c65d0367eb586c968edc655b7e4c601d35db358f8419047d
+size 9437