updated dataset card

README.md

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 # Dataset Card for "climate_fever_fixed"
 
+### Dataset Summary
+
+This dataset was created to aid our team in developing a model to more accurately perform climate change-related fact checking. We approach this task from a perspective heavily impacted 
+by the work of the [ClimateBERT](https://climatebert.ai/about) team. With that in mind, our team likewise leveraged a BERT Language model to solve this task. This dataset presents an 
+edited version of the [Climate_Fever](https://huggingface.co/datasets/climate_fever) dataset, hosted by HuggingFace. Climate_Fever is composed of climate-related documents 
+that have been annotated with labels related to fact-checking and misinformation. However, in the climate-plus project, we decided to modify the dataset to remove redundancy
+and keep only the essentials of a text-entailment problem: claim as the premise and evidence as the hypothesis.
+
+
+
+### Data Fields
+
+This dataset contains 7675 records, each of which is composed of several attributes:
+
+- `claim_id`: a `integer` feature, which serves as a unique identifier for each record/row. 
+- `claim`: a `string` feature, containes the raw text of a given climate-related claim. 
+- `evidence`: a `string` feature, which provides free text evidence that relates to the previously established claim.
+- `label`: a `class label` feature representing an assigned class, where values can either be 0: "supports", 1: "refutes" and 2: "not enough info".
+- `category`: a `string` feature, which provides additional detail about the particular focus of a given claim.
+
+<br>
+This dataset was then broken into train, test and validation sets to enable proper evaluation of our model. These splits contain the following amount of data:
+
+- `Train`: 4300 Records
+- `Test`: 1540 Records
+- `Val`: 1840 Records
+
+### Source Data
+
+This dataset represents an evolved version of the original [Climate_Fever](https://huggingface.co/datasets/climate_fever) dataset, hosted by HuggingFace. It was adapted to meet
+the needs of our team, as we attempted to solve a specific climate change-related task. The original dataset adopted the FEVER methodology, discussed in more detail [here](https://www.amazon.science/blog/the-fever-data-set-what-doesnt-kill-it-will-make-it-stronger).
+Their original dataset consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence 
+sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. 
+
+
+### Methodology
+
+This dataset was curated by our team to reduce redundancy and keep only the essentials of a text-entailment problem: claim as the premise and evidence as the hypothesis. 
+For each given claim, there are multiple sentences of evidence. We decided to expand the one-to-many relation to one-to-one. 
+This resulted in a modified version of the climate_fever dataset that includes only one evidence sentence per claim.
+
+
+### Languages
+
+The text contained in the dataset is entirely in English, as found in the real-world financial disclosures identified by the TCFD. The associated BCP-47 code is [`en`](https://www.techonthenet.com/js/language_tags.php), to ensure clear labeling of language usage for downstream tasks and other future applications.
+
 [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)