Update README.md

README.md

@@ -1,53 +1,19 @@
 ---
-language:
-- en
+language: en
+tags: 
+- deberta-v1
+- deberta-mnli
+tasks: mnli
+thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
 license: mit
-tags:
-- generated_from_trainer
-datasets:
-- glue
-metrics:
-- accuracy
-model-index:
-- name: mnlilearn
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: GLUE MNLI
-      type: glue
-      args: mnli
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.9175142392188771
+pipeline_tag: zero-shot-classification
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# mnlilearn
-
 This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the GLUE MNLI dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.4103
 - Accuracy: 0.9175
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -65,12 +31,4 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
 | 0.3631        | 1.0   | 49088 | 0.3129          | 0.9130   |
-| 0.2267        | 2.0   | 98176 | 0.4157          | 0.9153   |
-
-
-### Framework versions
-
-- Transformers 4.13.0.dev0
-- Pytorch 1.10.0
-- Datasets 1.15.2.dev0
-- Tokenizers 0.10.3
+| 0.2267        | 2.0   | 98176 | 0.4157          | 0.9153   |