Update README.md

README.md

@@ -8,7 +8,27 @@ metrics:
 - f1
 model-index:
 - name: finetuning-DistillBERT-amazon-polarity
-  results: []
+  results:
+  - task:
+      type: text-classification
+      name: Text Classification
+    dataset:
+      name: amazon_polarity
+      type: sentiment
+      args: default
+    metrics:
+    - type: accuracy
+      value: 0.9166666666666666
+      name: Accuracy
+    - type: loss
+      value: 0.1919892132282257
+      name: Loss
+    - type: f1
+      value: 0.9169435215946843
+      name: F1
+datasets:
+- amazon_polarity
+pipeline_tag: text-classification
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,7 +36,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # finetuning-DistillBERT-amazon-polarity
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on [Amazon Polarity](https://huggingface.co/datasets/amazon_polarity) dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.1920
 - Accuracy: 0.9167
@@ -56,4 +76,4 @@ The following hyperparameters were used during training:
 - Transformers 4.38.1
 - Pytorch 2.1.0+cu121
 - Datasets 2.18.0
-- Tokenizers 0.15.2
+- Tokenizers 0.15.2