update model card README.md

README.md

@@ -4,9 +4,34 @@ tags:
 - generated_from_trainer
 datasets:
 - skript
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: wikineural-multilingual-ner-finetuned-ner
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: skript
+      type: skript
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9013505175841503
+    - name: Recall
+      type: recall
+      value: 0.9308318584070796
+    - name: F1
+      type: f1
+      value: 0.9158539983282251
+    - name: Accuracy
+      type: accuracy
+      value: 0.9658385093167702
 ---
 
 <!-- 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 [Babelscape/wikineural-multilingual-ner](https://huggingface.co/Babelscape/wikineural-multilingual-ner) on the skript dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.1202
-- eval_precision: 0.8561
-- eval_recall: 0.8932
-- eval_f1: 0.8743
-- eval_accuracy: 0.9637
-- eval_runtime: 235.7895
-- eval_samples_per_second: 4.334
-- eval_steps_per_second: 0.271
-- epoch: 2.0
-- step: 596
+- Loss: 0.1219
+- Precision: 0.9014
+- Recall: 0.9308
+- F1: 0.9159
+- Accuracy: 0.9658
 
 ## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 298  | 0.1208          | 0.9016    | 0.8988 | 0.9002 | 0.9604   |
+| 0.118         | 2.0   | 596  | 0.1152          | 0.9016    | 0.9210 | 0.9112 | 0.9645   |
+| 0.118         | 3.0   | 894  | 0.1219          | 0.9014    | 0.9308 | 0.9159 | 0.9658   |
+
+
 ### Framework versions
 
 - Transformers 4.20.1