Training completed!

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.867816091954023
+      value: 0.8738244514106583
     - name: F1
       type: f1
-      value: 0.4862665310274669
+      value: 0.4990403071017275
 ---
 
 <!-- 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: 0.5043
-- Accuracy: 0.8678
-- F1: 0.4863
+- Loss: 0.4666
+- Accuracy: 0.8738
+- F1: 0.4990
 
 ## Model description
 
@@ -63,15 +63,16 @@ 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: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 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 |
+| 0.8992        | 1.0   | 61   | 0.6227          | 0.8404   | 0.4295 |
+| 0.5484        | 2.0   | 122  | 0.5143          | 0.8631   | 0.4784 |
+| 0.4243        | 3.0   | 183  | 0.4757          | 0.8710   | 0.4985 |
+| 0.3599        | 4.0   | 244  | 0.4666          | 0.8738   | 0.4990 |
 
 
 ### Framework versions