update model card README.md

README.md

@@ -2,9 +2,36 @@
 license: mit
 tags:
 - generated_from_trainer
+datasets:
+- plo_dunfiltered_config
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: roberta-large-finetuned-ner
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: plo_dunfiltered_config
+      type: plo_dunfiltered_config
+      args: PLODunfiltered
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9662545190541101
+    - name: Recall
+      type: recall
+      value: 0.9627013733169376
+    - name: F1
+      type: f1
+      value: 0.9644746737300262
+    - name: Accuracy
+      type: accuracy
+      value: 0.9607518572002093
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -12,7 +39,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # roberta-large-finetuned-ner
 
-This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
+This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the plo_dunfiltered_config dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1393
+- Precision: 0.9663
+- Recall: 0.9627
+- F1: 0.9645
+- Accuracy: 0.9608
 
 ## Model description
 
@@ -39,6 +72,18 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 6
 
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1281        | 1.0   | 14233 | 0.1300          | 0.9557    | 0.9436 | 0.9496 | 0.9457   |
+| 0.1056        | 2.0   | 28466 | 0.1076          | 0.9620    | 0.9552 | 0.9586 | 0.9545   |
+| 0.0904        | 3.0   | 42699 | 0.1054          | 0.9655    | 0.9585 | 0.9620 | 0.9583   |
+| 0.0743        | 4.0   | 56932 | 0.1145          | 0.9658    | 0.9602 | 0.9630 | 0.9593   |
+| 0.0523        | 5.0   | 71165 | 0.1206          | 0.9664    | 0.9619 | 0.9641 | 0.9604   |
+| 0.044         | 6.0   | 85398 | 0.1393          | 0.9663    | 0.9627 | 0.9645 | 0.9608   |
+
+
 ### Framework versions
 
 - Transformers 4.18.0