update model card README.md

README.md

@@ -4,36 +4,9 @@ tags:
 - generated_from_trainer
 datasets:
 - mim_gold_ner
-metrics:
-- precision
-- recall
-- f1
-- accuracy
-widget:
-- text: systurnar guðrún og monique voru einar á báti umkringdar eik og víði með þá einu ósk að sameinast fjölskyldu sinni sem fór í smárabíó að horfa á jim carey leika í the eternal sunshine of the spotless mind.
 model-index:
 - name: IceBERT-finetuned-ner
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: mim_gold_ner
-      type: mim_gold_ner
-      args: mim-gold-ner
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.8396080453842186
-    - name: Recall
-      type: recall
-      value: 0.7974137931034483
-    - name: F1
-      type: f1
-      value: 0.8179671406320655
-    - name: Accuracy
-      type: accuracy
-      value: 0.979332840486103
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,13 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # IceBERT-finetuned-ner
 
-This model is a fine-tuned version of [vesteinn/IceBERT](https://huggingface.co/vesteinn/IceBERT) on the mim_gold_ner dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1048
-- Precision: 0.8396
-- Recall: 0.7974
-- F1: 0.8180
-- Accuracy: 0.9793
+This model is a fine-tuned version of [eliasbe/IceBERT-finetuned-ner](https://huggingface.co/eliasbe/IceBERT-finetuned-ner) on the mim_gold_ner dataset.
 
 ## Model description
 
@@ -74,18 +41,9 @@ 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 |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0739        | 1.0   | 2904 | 0.1219          | 0.8060    | 0.7621 | 0.7834 | 0.9750   |
-| 0.0438        | 2.0   | 5808 | 0.1130          | 0.8233    | 0.7919 | 0.8073 | 0.9772   |
-| 0.0317        | 3.0   | 8712 | 0.1048          | 0.8396    | 0.7974 | 0.8180 | 0.9793   |
-
-
 ### Framework versions
 
-- Transformers 4.11.1
+- Transformers 4.11.2
 - Pytorch 1.9.0+cu102
 - Datasets 1.12.1
 - Tokenizers 0.10.3