End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.8117213736323259
+      value: 0.8465303458777463
     - name: Recall
       type: recall
-      value: 0.8382369392549502
+      value: 0.870679046873252
     - name: F1
       type: f1
-      value: 0.8247660979636764
+      value: 0.8584348977003253
     - name: Accuracy
       type: accuracy
-      value: 0.9613166632246175
+      value: 0.9670516466233497
 ---
 
 <!-- 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 [huawei-noah/TinyBERT_General_4L_312D](https://huggingface.co/huawei-noah/TinyBERT_General_4L_312D) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1547
-- Precision: 0.8117
-- Recall: 0.8382
-- F1: 0.8248
-- Accuracy: 0.9613
+- Loss: 0.1232
+- Precision: 0.8465
+- Recall: 0.8707
+- F1: 0.8584
+- Accuracy: 0.9671
 
 ## Model description
 
@@ -73,15 +73,17 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.5069        | 1.0   | 878  | 0.2184          | 0.7396    | 0.7742 | 0.7565 | 0.9481   |
-| 0.2068        | 2.0   | 1756 | 0.1667          | 0.8115    | 0.8201 | 0.8158 | 0.9593   |
-| 0.166         | 3.0   | 2634 | 0.1547          | 0.8117    | 0.8382 | 0.8248 | 0.9613   |
+| 0.5173        | 1.0   | 878  | 0.2116          | 0.7429    | 0.7756 | 0.7589 | 0.9493   |
+| 0.196         | 2.0   | 1756 | 0.1528          | 0.8262    | 0.8383 | 0.8323 | 0.9620   |
+| 0.1444        | 3.0   | 2634 | 0.1355          | 0.8447    | 0.8606 | 0.8526 | 0.9652   |
+| 0.116         | 4.0   | 3512 | 0.1255          | 0.8452    | 0.8660 | 0.8555 | 0.9663   |
+| 0.1116        | 5.0   | 4390 | 0.1232          | 0.8465    | 0.8707 | 0.8584 | 0.9671   |
 
 
 ### Framework versions

runs/Nov11_15-29-13_73de3ff1df3d/events.out.tfevents.1731338961.73de3ff1df3d.650.0

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+size 9800

runs/Nov11_15-29-13_73de3ff1df3d/events.out.tfevents.1731339235.73de3ff1df3d.650.1

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