End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.8726823238566132
+      value: 0.8732321490169024
     - name: Recall
       type: recall
-      value: 0.875
+      value: 0.8964235127478754
     - name: F1
       type: f1
-      value: 0.8738396251436654
+      value: 0.8846758692993185
     - name: Accuracy
       type: accuracy
-      value: 0.9719608054269409
+      value: 0.9751049854635512
 ---
 
 <!-- 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 [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2170
-- Precision: 0.8727
-- Recall: 0.875
-- F1: 0.8738
-- Accuracy: 0.9720
+- Loss: nan
+- Precision: 0.8732
+- Recall: 0.8964
+- F1: 0.8847
+- Accuracy: 0.9751
 
 ## Model description
 
@@ -79,8 +79,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0728        | 1.0   | 3922 | 0.2114          | 0.8604    | 0.8688 | 0.8646 | 0.9699   |
-| 0.0379        | 2.0   | 7844 | 0.2170          | 0.8727    | 0.875  | 0.8738 | 0.9720   |
+| 0.0605        | 1.0   | 3922 | nan             | 0.8717    | 0.8877 | 0.8796 | 0.9742   |
+| 0.0296        | 2.0   | 7844 | nan             | 0.8732    | 0.8964 | 0.8847 | 0.9751   |
 
 
 ### Framework versions

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:4137bd4c7129849dcf1a1969602541e47b88f37c8b1a920a084eb5939b569653
 size 260843682