Model save

README.md

@@ -3,8 +3,6 @@ license: mit
 base_model: microsoft/deberta-v3-small
 tags:
 - generated_from_trainer
-datasets:
-- nbroad/company_names
 metrics:
 - precision
 - recall
@@ -12,26 +10,7 @@ metrics:
 - accuracy
 model-index:
 - name: deberta-v3-small-company-names
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: nbroad/company_names
-      type: nbroad/company_names
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.7687575810084907
-    - name: Recall
-      type: recall
-      value: 0.7920906980896268
-    - name: F1
-      type: f1
-      value: 0.780249736194161
-    - name: Accuracy
-      type: accuracy
-      value: 0.9766189637193916
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -39,7 +18,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # deberta-v3-small-company-names
 
-This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the nbroad/company_names dataset.
+This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.0707
 - Precision: 0.7688

pytorch_model.bin

@@ -1,3 +1,3 @@
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 size 565262061