update model card README.md

README.md

@@ -4,9 +4,34 @@ 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
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9357509521443947
+    - name: Recall
+      type: recall
+      value: 0.9510265903736116
+    - name: F1
+      type: f1
+      value: 0.9433269343126617
+    - name: Accuracy
+      type: accuracy
+      value: 0.9861953258374051
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,16 +41,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 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:
-- eval_loss: 0.0686
-- eval_precision: 0.9312
-- eval_recall: 0.9456
-- eval_f1: 0.9384
-- eval_accuracy: 0.9844
-- eval_runtime: 8.1792
-- eval_samples_per_second: 397.472
-- eval_steps_per_second: 49.76
-- epoch: 2.0
-- step: 3512
+- Loss: 0.0793
+- Precision: 0.9358
+- Recall: 0.9510
+- F1: 0.9433
+- Accuracy: 0.9862
 
 ## Model description
 
@@ -52,6 +72,15 @@ 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0247        | 1.0   | 1756 | 0.0798          | 0.9269    | 0.9435 | 0.9351 | 0.9840   |
+| 0.0136        | 2.0   | 3512 | 0.0776          | 0.9309    | 0.9495 | 0.9401 | 0.9857   |
+| 0.0097        | 3.0   | 5268 | 0.0793          | 0.9358    | 0.9510 | 0.9433 | 0.9862   |
+
+
 ### Framework versions
 
 - Transformers 4.16.2