NER_Pittsburgh_TAA

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9395179124281291
+      value: 0.9429236395877203
     - name: Recall
       type: recall
-      value: 0.9505537532162435
+      value: 0.9517843159190066
     - name: F1
       type: f1
-      value: 0.9450036145248291
+      value: 0.9473332591025497
     - name: Accuracy
       type: accuracy
-      value: 0.9864965764849795
+      value: 0.9867030994328562
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0805
-- Precision: 0.9395
-- Recall: 0.9506
-- F1: 0.9450
-- Accuracy: 0.9865
+- Loss: 0.0860
+- Precision: 0.9429
+- Recall: 0.9518
+- F1: 0.9473
+- Accuracy: 0.9867
 
 ## Model description
 
@@ -79,11 +79,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 439  | 0.0774          | 0.9424    | 0.9455 | 0.9439 | 0.9855   |
-| 0.0061        | 2.0   | 878  | 0.0741          | 0.9399    | 0.9475 | 0.9437 | 0.9863   |
-| 0.0042        | 3.0   | 1317 | 0.0784          | 0.9355    | 0.9479 | 0.9417 | 0.9855   |
-| 0.0026        | 4.0   | 1756 | 0.0789          | 0.9409    | 0.9490 | 0.9449 | 0.9865   |
-| 0.0016        | 5.0   | 2195 | 0.0805          | 0.9395    | 0.9506 | 0.9450 | 0.9865   |
+| No log        | 1.0   | 439  | 0.0863          | 0.9437    | 0.9444 | 0.9440 | 0.9861   |
+| 0.0024        | 2.0   | 878  | 0.0995          | 0.9394    | 0.9442 | 0.9418 | 0.9852   |
+| 0.0021        | 3.0   | 1317 | 0.0904          | 0.9355    | 0.9463 | 0.9409 | 0.9856   |
+| 0.0012        | 4.0   | 1756 | 0.0835          | 0.9427    | 0.9514 | 0.9471 | 0.9867   |
+| 0.0009        | 5.0   | 2195 | 0.0860          | 0.9429    | 0.9518 | 0.9473 | 0.9867   |
 
 
 ### Framework versions

model.safetensors

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 size 435617620

runs/Jun13_15-41-46_53e1e73118f7/events.out.tfevents.1718293312.53e1e73118f7.799.2

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