Training completed!

README.md

@@ -6,6 +6,7 @@ tags:
 datasets:
 - conll2012_ontonotesv5
 metrics:
+- accuracy
 - f1
 model-index:
 - name: distilbert-NER-finetuned
@@ -20,9 +21,12 @@ model-index:
       split: validation
       args: english_v4
     metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.886927374301676
     - name: F1
       type: f1
-      value: 0.47876447876447875
+      value: 0.48622047244094485
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +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: 0.5652
-- F1: 0.4788
+- Loss: 0.4199
+- Accuracy: 0.8869
+- F1: 0.4862
 
 ## Model description
 
@@ -62,16 +67,16 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| 1.0541        | 1.0   | 81   | 0.7248          | 0.3931 |
-| 0.6283        | 2.0   | 162  | 0.6020          | 0.4621 |
-| 0.5061        | 3.0   | 243  | 0.5652          | 0.4788 |
+| 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 |
 
 
 ### Framework versions
 
 - Transformers 4.42.4
 - Pytorch 2.4.0+cu121
-- Datasets 2.21.0
+- Datasets 2.19.2
 - Tokenizers 0.19.1