Update README.md

README.md

@@ -16,14 +16,25 @@ model-index:
     metrics:
       - type: f1         
         value: 0.9992
+---
+
+# DistilBERT base uncased finetuned SST-2
 
+## Table of Contents
+- [Model Details](#model-details)
+- [How to Get Started With the Model](#how-to-get-started-with-the-model)
+- [Uses](#uses)
+- [Risks, Limitations and Biases](#risks-limitations-and-biases)
+- [Training](#training)
 
-Model Description: This model is a fine-tuned checkpoint of bert-large-uncased, fine-tuned on SST-2. This model reaches F1 of 99.92 on the dev set.
-Developed by: rttl labs
-Model Type: Text Classification
-Language(s): English
-License: Apache-2.0
-Resources for more information: 
-The model was pre-trained with task-adaptive pre-training (TAPT), with an increased masking rate, no corruption strategy, and WWM, following this paper.
-then fine-tuned on sst with subtrees 
-then fine-tuned on sst2
+## Model Details
+**Model Description:** This model is a fine-tune checkpoint of [DistilBERT-base-uncased](https://huggingface.co/distilbert-base-uncased), fine-tuned on SST-2.
+This model reaches an accuracy of 91.3 on the dev set (for comparison, Bert bert-base-uncased version reaches an accuracy of 92.7).
+- **Developed by:** Hugging Face
+- **Model Type:** Text Classification
+- **Language(s):** English
+- **License:** Apache-2.0
+- **Parent Model:** For more details about DistilBERT, we encourage users to check out [this model card](https://huggingface.co/distilbert-base-uncased).
+- **Resources for more information:**
+    - [Model Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/distilbert#transformers.DistilBertForSequenceClassification)
+    - [DistilBERT paper](https://arxiv.org/abs/1910.01108)