update model card README.md

README.md

@@ -4,9 +4,36 @@ tags:
 - generated_from_trainer
 datasets:
 - conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: bert-finetuned-ner
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      config: conll2003
+      split: train
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9338296112489661
+    - name: Recall
+      type: recall
+      value: 0.9500168293503871
+    - name: F1
+      type: f1
+      value: 0.9418536748143823
+    - name: Accuracy
+      type: accuracy
+      value: 0.9861364572908695
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,6 +42,12 @@ should probably proofread and complete it, then remove this comment. -->
 # bert-finetuned-ner
 
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0587
+- Precision: 0.9338
+- Recall: 0.9500
+- F1: 0.9419
+- Accuracy: 0.9861
 
 ## Model description
 
@@ -41,9 +74,18 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 3
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0889        | 1.0   | 1756 | 0.0711          | 0.9132    | 0.9297 | 0.9214 | 0.9809   |
+| 0.0338        | 2.0   | 3512 | 0.0597          | 0.9315    | 0.9475 | 0.9394 | 0.9860   |
+| 0.0184        | 3.0   | 5268 | 0.0587          | 0.9338    | 0.9500 | 0.9419 | 0.9861   |
+
+
 ### Framework versions
 
 - Transformers 4.25.1
-- Pytorch 1.13.0+cu116
+- Pytorch 1.13.1+cu116
 - Datasets 2.8.0
 - Tokenizers 0.13.2