End of training

README.md

@@ -26,16 +26,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.929140832595217
+      value: 0.9267484255883328
     - name: Recall
       type: recall
-      value: 0.9388074728716859
+      value: 0.9383599955252265
     - name: F1
       type: f1
-      value: 0.9339491402815647
+      value: 0.9325180655919956
     - name: Accuracy
       type: accuracy
-      value: 0.9840977330134876
+      value: 0.9837641190207635
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -45,11 +45,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0598
-- Precision: 0.9291
-- Recall: 0.9388
-- F1: 0.9339
-- Accuracy: 0.9841
+- Loss: 0.0601
+- Precision: 0.9267
+- Recall: 0.9384
+- F1: 0.9325
+- Accuracy: 0.9838
 
 ## Model description
 
@@ -80,9 +80,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.2506        | 1.0   | 878  | 0.0697          | 0.9086    | 0.9192 | 0.9139 | 0.9803   |
-| 0.0513        | 2.0   | 1756 | 0.0601          | 0.9261    | 0.9347 | 0.9303 | 0.9837   |
-| 0.0298        | 3.0   | 2634 | 0.0598          | 0.9291    | 0.9388 | 0.9339 | 0.9841   |
+| 0.2513        | 1.0   | 878  | 0.0707          | 0.9057    | 0.9181 | 0.9119 | 0.9799   |
+| 0.0519        | 2.0   | 1756 | 0.0604          | 0.9224    | 0.9369 | 0.9296 | 0.9833   |
+| 0.0306        | 3.0   | 2634 | 0.0601          | 0.9267    | 0.9384 | 0.9325 | 0.9838   |
 
 
 ### Framework versions

model.safetensors

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runs/Oct30_11-05-12_4a20cf935db3/events.out.tfevents.1730286368.4a20cf935db3.30.0

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