Update README.md

README.md

@@ -1,19 +1,23 @@
 ---
-license: apache-2.0
-base_model: distilbert-base-uncased
+language: "en"
 tags:
-- generated_from_trainer
-metrics:
-- accuracy
-model-index:
-- name: text_classification_model
-  results: []
+- distilbert
+- sentiment
+- positive
+- negative 
+- review
+- imdb
 ---
 
-<!-- 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. -->
+# Fine-tuned DistilBERT-base-uncased for IMDB Classification
 
-# text_classification_model
+# Model Description 
+
+DistilBERT is a transformer model that performs sentiment analysis. I fine-tuned the model on IMDB dataset with the purpose of classifying positive reviews from the bad ones. The model predicts these 2 classes. 
+
+The model is a fine-tuned version of [DistilBERT](https://huggingface.co/docs/transformers/model_doc/distilbert).
+
+It was fine-tuned on IMDB dataset [https://huggingface.co/datasets/imdb].
 
 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:
@@ -59,3 +63,7 @@ The following hyperparameters were used during training:
 - Pytorch 2.1.0+cu121
 - Datasets 2.17.0
 - Tokenizers 0.15.1
+
+# Contact
+
+Please reach out to [luca.flammia@gmail.com] if you have any questions or feedback.