update model card README.md

README.md

@@ -2,6 +2,8 @@
 license: apache-2.0
 tags:
 - generated_from_trainer
+datasets:
+- conll2003
 metrics:
 - precision
 - recall
@@ -9,7 +11,27 @@ metrics:
 - accuracy
 model-index:
 - name: bert-base-uncased-finetuned-ner
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9412415624654199
+    - name: Recall
+      type: recall
+      value: 0.9515605772457769
+    - name: F1
+      type: f1
+      value: 0.9463729417000445
+    - name: Accuracy
+      type: accuracy
+      value: 0.9869572815225507
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,13 +39,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert-base-uncased-finetuned-ner
 
-This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0898
-- Precision: 0.9065
-- Recall: 0.9226
-- F1: 0.9145
-- Accuracy: 0.9789
+- Loss: 0.0605
+- Precision: 0.9412
+- Recall: 0.9516
+- F1: 0.9464
+- Accuracy: 0.9870
 
 ## Model description
 
@@ -43,8 +65,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -54,14 +76,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1268        | 1.0   | 1123 | 0.0877          | 0.9052    | 0.8901 | 0.8976 | 0.9750   |
-| 0.0742        | 2.0   | 2246 | 0.0863          | 0.8954    | 0.9219 | 0.9085 | 0.9779   |
-| 0.0482        | 3.0   | 3369 | 0.0898          | 0.9065    | 0.9226 | 0.9145 | 0.9789   |
+| 0.0786        | 1.0   | 1756 | 0.0573          | 0.9274    | 0.9341 | 0.9307 | 0.9843   |
+| 0.039         | 2.0   | 3512 | 0.0566          | 0.9370    | 0.9472 | 0.9421 | 0.9863   |
+| 0.0217        | 3.0   | 5268 | 0.0605          | 0.9412    | 0.9516 | 0.9464 | 0.9870   |
 
 
 ### Framework versions
 
 - Transformers 4.14.1
-- Pytorch 1.6.0
+- Pytorch 1.10.1
 - Datasets 1.17.0
 - Tokenizers 0.10.3