Training complete

README.md

@@ -5,9 +5,36 @@ 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: validation
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9317693705600528
+    - name: Recall
+      type: recall
+      value: 0.9491753618310333
+    - name: F1
+      type: f1
+      value: 0.9403918299291371
+    - name: Accuracy
+      type: accuracy
+      value: 0.9865338199799847
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +43,12 @@ 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: 0.0595
+- Precision: 0.9318
+- Recall: 0.9492
+- F1: 0.9404
+- Accuracy: 0.9865
 
 ## Model description
 
@@ -40,10 +73,15 @@ 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: 0
+- num_epochs: 3
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0757        | 1.0   | 1756 | 0.0603          | 0.9045    | 0.9320 | 0.9180 | 0.9817   |
+| 0.0382        | 2.0   | 3512 | 0.0615          | 0.9334    | 0.9460 | 0.9397 | 0.9854   |
+| 0.0213        | 3.0   | 5268 | 0.0595          | 0.9318    | 0.9492 | 0.9404 | 0.9865   |
 
 
 ### Framework versions