
# Model Card for Model ID

Model fine tuned with LoRA on an Amharic Corpus of data collected from public telegram channels and groups.



## Model Details

### Model Description


- **Developed by:** [Biniyam Ajaw, Elias Assamnew]
- **Funded by:** [10 Academy]
- **Shared by [optional]:** [Biniyam Ajaw]
- **Model type:** [Text Generation]
- **Language(s) (NLP):** [Amharic - English]
- **License:** [MIT]
- **Finetuned from model [optional]:** [NousResearch-Llama2-7B-hf]

## Uses

The model is still in development and significantly lacks training data so it might not generate contents the way you want it to.


### Downstream Use [optional]

You can fine tune this model on labeled data for a specific domain. To get more pleasing results.


## Bias, Risks, and Limitations

The model is highly biased towards generating news content.
The model might repeat specific words because it is trained on a cleaned but unfiltered data because of the lack of tokens.



### Recommendations

The model is better of if you train it on labeled data if you want it to generate a content.

- PEFT 0.7.2.dev0
{"language": ["am"], "license": "mit", "library_name": "peft", "datasets": ["BiniyamAjaw/amharic_dataset_v2"], "metrics": ["bleu"], "base_model": "NousResearch/Llama-2-7b-hf", "pipeline_tag": "text-generation"}
peft safetensors text-generation am dataset:BiniyamAjaw/amharic_dataset_v2 base_model:NousResearch/Llama-2-7b-hf license:mit region:us