Training completed!

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.886927374301676
+      value: 0.867816091954023
     - name: F1
       type: f1
-      value: 0.48622047244094485
+      value: 0.4862665310274669
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on the conll2012_ontonotesv5 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4199
-- Accuracy: 0.8869
-- F1: 0.4862
+- Loss: 0.5043
+- Accuracy: 0.8678
+- F1: 0.4863
 
 ## Model description
 
@@ -69,9 +69,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.7537        | 1.0   | 81   | 0.5239          | 0.8635   | 0.4186 |
-| 0.4601        | 2.0   | 162  | 0.4479          | 0.88     | 0.4790 |
-| 0.3613        | 3.0   | 243  | 0.4199          | 0.8869   | 0.4862 |
+| 0.9019        | 1.0   | 61   | 0.6286          | 0.8406   | 0.4223 |
+| 0.5594        | 2.0   | 122  | 0.5302          | 0.8605   | 0.4567 |
+| 0.4537        | 3.0   | 183  | 0.5043          | 0.8678   | 0.4863 |
 
 
 ### Framework versions