Create README.md

README.md

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+---
+license: cc-by-2.0
+datasets:
+- mbazaNLP/NMT_Tourism_parallel_data_en_kin
+- mbazaNLP/NMT_Education_parallel_data_en_kin
+- mbazaNLP/Kinyarwanda_English_parallel_dataset
+language:
+- en
+- rw
+library_name: transformers
+---
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is a Machine Translation model, finetuned from [NLLB](https://huggingface.co/facebook/nllb-200-distilled-1.3B)-200's distilled 1.3B model, it is meant to be used in machine translation for education-related data.
+
+
+
+- **Finetuning code repository:** the code used to finetune this model can be found [here](https://github.com/Digital-Umuganda/twb_nllb_finetuning)
+
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+
+### Training Procedure 
+
+The model was finetuned on three datasets; a [general](https://huggingface.co/datasets/mbazaNLP/Kinyarwanda_English_parallel_dataset) purpose dataset, a [tourism](https://huggingface.co/datasets/mbazaNLP/NMT_Tourism_parallel_data_en_kin), and an [education](https://huggingface.co/datasets/mbazaNLP/NMT_Education_parallel_data_en_kin) dataset.
+The model was finetuned on an A100 40GB GPU for two epochs.
+
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+
+#### Testing Data
+
+<!-- This should link to a Data Card if possible. -->
+
+
+#### Metrics
+
+Model performance was measured using BLEU, spBLEU, TER, and chrF++ metrics.
+
+### Results
+
+
+
+
+