update model card README.md

README.md

@@ -2,9 +2,36 @@
 license: apache-2.0
 tags:
 - generated_from_trainer
+datasets:
+- plo_dunfiltered_config
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: albert-large-v2-finetuned-ner_with_callbacks
-  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: 0.9655166719570215
+    - name: Recall
+      type: recall
+      value: 0.9608483288141474
+    - name: F1
+      type: f1
+      value: 0.9631768437660728
+    - name: Accuracy
+      type: accuracy
+      value: 0.9589410429715819
 ---
 
 <!-- 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. -->
 
 # albert-large-v2-finetuned-ner_with_callbacks
 
-This model is a fine-tuned version of [albert-large-v2](https://huggingface.co/albert-large-v2) on an unknown dataset.
+This model is a fine-tuned version of [albert-large-v2](https://huggingface.co/albert-large-v2) on the plo_dunfiltered_config dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1235
+- Precision: 0.9655
+- Recall: 0.9608
+- F1: 0.9632
+- Accuracy: 0.9589
 
 ## Model description
 
@@ -39,6 +72,24 @@ 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1377        | 0.49  | 7000  | 0.1294          | 0.9563    | 0.9422 | 0.9492 | 0.9436   |
+| 0.1244        | 0.98  | 14000 | 0.1165          | 0.9589    | 0.9504 | 0.9546 | 0.9499   |
+| 0.107         | 1.48  | 21000 | 0.1140          | 0.9603    | 0.9509 | 0.9556 | 0.9511   |
+| 0.1088        | 1.97  | 28000 | 0.1086          | 0.9613    | 0.9551 | 0.9582 | 0.9536   |
+| 0.0918        | 2.46  | 35000 | 0.1059          | 0.9617    | 0.9582 | 0.9600 | 0.9556   |
+| 0.0847        | 2.95  | 42000 | 0.1067          | 0.9620    | 0.9586 | 0.9603 | 0.9559   |
+| 0.0734        | 3.44  | 49000 | 0.1188          | 0.9646    | 0.9588 | 0.9617 | 0.9574   |
+| 0.0725        | 3.93  | 56000 | 0.1065          | 0.9660    | 0.9599 | 0.9630 | 0.9588   |
+| 0.0547        | 4.43  | 63000 | 0.1273          | 0.9662    | 0.9602 | 0.9632 | 0.9590   |
+| 0.0542        | 4.92  | 70000 | 0.1235          | 0.9655    | 0.9608 | 0.9632 | 0.9589   |
+| 0.0374        | 5.41  | 77000 | 0.1401          | 0.9647    | 0.9613 | 0.9630 | 0.9586   |
+| 0.0417        | 5.9   | 84000 | 0.1380          | 0.9641    | 0.9622 | 0.9632 | 0.9588   |
+
+
 ### Framework versions
 
 - Transformers 4.18.0