Update README.md

README.md

@@ -34,14 +34,18 @@ Also, its worth noting that the model repo doesnt have a ```tokenizer.json```, a
 instead of AutoModel or other modules in Transformer.
 
 ## Source of Funding for this Work
-The dataset that was used to fine-tune this model as well as resources for compute were provided by 
-[Opportunity Internation](https://www.globalcitizen.org/en/partners/opportunity-international/?gad_source=1&gbraid=0AAAAACnN8MzEIzvf0oKqHW5bw14A4IvGY&gclid=CjwKCAjw9p24BhB_EiwA8ID5Bptp-7RgECcozDIe_6Owjb2g0wClWOKv4-NsEdtXpKx4FGPvOlBPQBoC9SMQAvD_BwE). Mor
+The dataset used to fine-tune this model, as well as the compute resources, were provided by [Opportunity International](https://www.globalcitizen.org/en/partners/opportunity-international/?gad_source=1&gbraid=0AAAAACnN8MzEIzvf0oKqHW5bw14A4IvGY&gclid=CjwKCAjw9p24BhB_EiwA8ID5Bptp-7RgECcozDIe_6Owjb2g0wClWOKv4-NsEdtXpKx4FGPvOlBPQBoC9SMQAvD_BwE).  
+This was part of a project in Malawi aimed at supporting the deployment of an LLM-based chatbot for agriculture, with the capability to handle voice interactions in the local language, Chichewa. 
+A total of 30 hours was collected for this dataset but due to data quality issues, only 25 hours was used. 
+About 30 minutes was also removed to be used as hold-out for further model evaluation.
 
 ## Training and evaluation data
 
 More information needed
 
 ## Training procedure
+Most of the training for this model involved trying to varying speech dataset sizes (5 hours, 10 hours up to 24 hours). 
+As such, the different model commits represent different data sizes. More details will be added to each model commit.
 
 ### Training hyperparameters