update model card README.md

README.md

@@ -2,9 +2,38 @@
 license: apache-2.0
 tags:
 - generated_from_trainer
+datasets:
+- plod-filtered
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: albert-base-v2-finetuned-ner
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: plod-filtered
+      type: plod-filtered
+      config: PLODfiltered
+      split: validation
+      args: PLODfiltered
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.988973631766888
+    - name: Recall
+      type: recall
+      value: 0.988142815877984
+    - name: F1
+      type: f1
+      value: 0.9885580492613874
+    - name: Accuracy
+      type: accuracy
+      value: 0.9883807619910069
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -12,7 +41,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # albert-base-v2-finetuned-ner
 
-This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
+This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the plod-filtered dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0319
+- Precision: 0.9890
+- Recall: 0.9881
+- F1: 0.9886
+- Accuracy: 0.9884
 
 ## Model description
 
@@ -39,6 +74,14 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 2
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0649        | 1.0   | 3018 | 0.0471          | 0.9838    | 0.9814 | 0.9826 | 0.9818   |
+| 0.0442        | 2.0   | 6036 | 0.0319          | 0.9890    | 0.9881 | 0.9886 | 0.9884   |
+
+
 ### Framework versions
 
 - Transformers 4.22.2