kaustavbhattacharjee/finetuning-DistillBERT-amazon-polarity

README.md

@@ -8,26 +8,7 @@ metrics:
 - f1
 model-index:
 - name: finetuning-DistillBERT-amazon-polarity
-  results:
-  - task:
-      type: text-classification
-      name: Text Classification
-    dataset:
-      name: amazon_polarity
-      type: sentiment
-      args: default
-    metrics:
-    - type: accuracy
-      value: 0.89
-      name: Accuracy
-    - type: loss
-      value: 0.4167933762073517
-      name: Loss
-    - type: f1
-      value: 0.8842105263157894
-      name: F1
-datasets:
-- amazon_polarity
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,12 +16,11 @@ 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 the [Amazon Polarity](https://huggingface.co/datasets/amazon_polarity) dataset.
-This version used 1000 samples to train and 100 samples to test the results.
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4168
-- Accuracy: 0.89
-- F1: 0.8842
+- Loss: 0.1920
+- Accuracy: 0.9167
+- F1: 0.9169
 
 ## Model description
 
@@ -76,4 +56,4 @@ 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

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