Training in progress, step 464

README.md

@@ -31,25 +31,25 @@ model-index:
       type: fineweb_c_eval
     metrics:
     - type: accuracy
-      value: 0.9013671875
+      value: 0.91015625
       name: Accuracy
     - type: accuracy_threshold
-      value: 0.8407575488090515
+      value: 0.9219144582748413
       name: Accuracy Threshold
     - type: f1
-      value: 0.6757493188010899
+      value: 0.6866666666666666
       name: F1
     - type: f1_threshold
-      value: 0.49566662311553955
+      value: 0.8624649047851562
       name: F1 Threshold
     - type: precision
-      value: 0.62
+      value: 0.7744360902255639
       name: Precision
     - type: recall
-      value: 0.7425149700598802
+      value: 0.6167664670658682
       name: Recall
     - type: average_precision
-      value: 0.7125866664018541
+      value: 0.7401881464737206
       name: Average Precision
 ---
 
@@ -110,7 +110,7 @@ pairs = [
 ]
 scores = model.predict(pairs)
 print(scores)
-# [0.0136 0.9988 0.0103 0.0052 0.0117]
+# [0.0272 0.9999 0.0107 0.0086 0.077 ]
 
 # Or rank different texts based on similarity to a single text
 ranks = model.rank(
@@ -161,13 +161,13 @@ You can finetune this model on your own dataset.
 
 | Metric                | Value      |
 |:----------------------|:-----------|
-| accuracy              | 0.9014     |
-| accuracy_threshold    | 0.8408     |
-| f1                    | 0.6757     |
-| f1_threshold          | 0.4957     |
-| precision             | 0.62       |
-| recall                | 0.7425     |
-| **average_precision** | **0.7126** |
+| accuracy              | 0.9102     |
+| accuracy_threshold    | 0.9219     |
+| f1                    | 0.6867     |
+| f1_threshold          | 0.8625     |
+| precision             | 0.7744     |
+| recall                | 0.6168     |
+| **average_precision** | **0.7402** |
 
 <!--
 ## Bias, Risks and Limitations
@@ -432,12 +432,23 @@ You can finetune this model on your own dataset.
 | 1.3702 | 396  | 0.4614        | -               | -                                |
 | 1.3910 | 402  | 0.3266        | -               | -                                |
 | 1.4048 | 406  | -             | 0.7257          | 0.7126                           |
+| 1.4118 | 408  | 0.4361        | -               | -                                |
+| 1.4325 | 414  | 0.4928        | -               | -                                |
+| 1.4533 | 420  | 0.4441        | -               | -                                |
+| 1.4740 | 426  | 0.2820        | -               | -                                |
+| 1.4948 | 432  | 0.5146        | -               | -                                |
+| 1.5156 | 438  | 0.6355        | -               | -                                |
+| 1.5363 | 444  | 0.4136        | -               | -                                |
+| 1.5571 | 450  | 0.2685        | -               | -                                |
+| 1.5779 | 456  | 0.6273        | -               | -                                |
+| 1.5986 | 462  | 0.5283        | -               | -                                |
+| 1.6055 | 464  | -             | 0.6483          | 0.7402                           |
 
 
 ### Training Time
-- **Training**: 6.5 minutes
-- **Evaluation**: 2.4 minutes
-- **Total**: 9.0 minutes
+- **Training**: 7.5 minutes
+- **Evaluation**: 2.8 minutes
+- **Total**: 10.2 minutes
 
 ### Framework Versions
 - Python: 3.12.12

eval/CrossEncoderClassificationEvaluator_fineweb_c_eval_results.csv

@@ -6,3 +6,4 @@ epoch,steps,Accuracy,Accuracy_Threshold,F1,F1_Threshold,Precision,Recall,Average
 1.0034602076124568,290,0.8837890625,0.81047595,0.6024844720496895,0.714628,0.6258064516129033,0.5808383233532934,0.6180374262832308
 1.2041522491349481,348,0.90234375,0.7725241,0.6426229508196721,0.6013595,0.7101449275362319,0.5868263473053892,0.696727465964923
 1.4048442906574394,406,0.9013671875,0.84075755,0.6757493188010899,0.49566662,0.62,0.7425149700598802,0.7125866664018541
+1.6055363321799307,464,0.91015625,0.92191446,0.6866666666666666,0.8624649,0.7744360902255639,0.6167664670658682,0.7401881464737206

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bc0c1e4d699357e02cde7574bd71f82a72ff4ba0e84fcdc7e88bb00bc2a23af9
+oid sha256:ac1ceac343b899a646fb41aefdcfaa773282f9e705396e2d3dbd903f1ee38a9d
 size 1230138348