Update README.md

README.md

@@ -7,30 +7,28 @@ tags:
 model-index:
 - name: wb-climate-regression
   results: []
+datasets:
+- alex-miller/wb-climate-percentage
 ---
 
-<!-- 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. -->
 
 # wb-climate-regression
 
-This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on an unknown dataset.
+This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on the [alex-miller/wb-climate-percentage](https://huggingface.co/alex-miller/wb-climate-percentage) dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.0309
 
 ## Model description
 
-More information needed
+A regression model that embeds text using a fine-tuned bert-base-multilingual-uncased and uses the AutoModelForSequenceClassification class to output predicted percentage climate finance, climate adaptation finance, and climate mitigation finance.
 
 ## Intended uses & limitations
 
-More information needed
+Intended to regress World Bank project development objectives and abstracts. Not yet validated against project descriptions written outside of the World Bank project API V3.
 
 ## Training and evaluation data
 
-More information needed
-
-## Training procedure
+Data was collected automatically from the World Bank project API V3. For full code on how data was gathered, see: [https://github.com/akmiller01/world-bank-climate-regression/blob/main/code/wb_api_climate.py](https://github.com/akmiller01/world-bank-climate-regression/blob/main/code/wb_api_climate.py)
 
 ### Training hyperparameters
 
@@ -74,4 +72,4 @@ The following hyperparameters were used during training:
 - Transformers 4.44.2
 - Pytorch 2.5.0+cu121
 - Datasets 3.1.0
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1