Update README.md

README.md

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-<!-- This model card has been generated automatically according to the information Keras had access to. You should
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 # distilbert-base-future
 ## Table of Contents
 
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 - [Training and evaluation data](#training_and_evaluation_data)
 - [Training procedure](#training_procedure)
 
-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 the [future-statements dataset](https://huggingface.co/datasets/fidsinn/future-statements).
 It achieves the following results on the evaluation set:
 - Train Loss: 0.1142
 - Train Sparse Categorical Accuracy: 0.9613
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 ## Model description
 
-More information needed
+- The model was created by graduate students [D. Baradari](https://huggingface.co/Dunya), [F. Bartels](https://huggingface.co/fidsinn), A. Dewald, [J. Peters](https://huggingface.co/jpeters92) as part of a data science module of the University of Leipzig.
+- Model was created on 11/08/22.
+- This is version 1.0
+- The model is a text classification model which is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased)
+- Questions and comments can be send via the [community tab](https://huggingface.co/fidsinn/distilbert-base-future/discussions)
 
 ## Intended uses & limitations
 
-More information needed
+- The primary intended use is the classification of input into a future or non-future sentence/statement.
+- The model is primarily intended to be used by researchers to filter or label a large number of sentences according to the grammatical tense of the input.
 
 ## Training and evaluation data
 
-More information needed
+- [Distilbert-base-future model](https://huggingface.co/fidsinn/distilbert-base-future) was trained and evaluated on the [future-statements dataset](https://huggingface.co/datasets/fidsinn/future-statements).
+- [future-statements](https://huggingface.co/datasets/fidsinn/future-statements) is a dataset collected manually and automatically by graduate students [D. Baradari](https://huggingface.co/Dunya), [F. Bartels](https://huggingface.co/fidsinn), A. Dewald, [J. Peters](https://huggingface.co/jpeters92) of the University of Leipzig.
+- We collected 2500 statements, 50% of which relate to future events and 50% of which relate to non-future events.
+- The sole purpose of the dataset was the fine-tuning process of this model.
+- Additional information on the dataset can be found on Huggingface: [future-statements dataset](https://huggingface.co/datasets/fidsinn/future-statements).
 
 ## Training procedure