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--- |
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language: |
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- en |
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- hi |
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license: llama2 |
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library_name: transformers |
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tags: |
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- hindi |
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- 'english ' |
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- Bilingual |
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datasets: |
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- sarvamai/samvaad-hi-v1 |
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pipeline_tag: text-generation |
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model-index: |
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- name: Gaja-v2.00 |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 51.79 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=damerajee/Gaja-v2.00 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 75.79 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=damerajee/Gaja-v2.00 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 40.69 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=damerajee/Gaja-v2.00 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 41.5 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=damerajee/Gaja-v2.00 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 71.9 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=damerajee/Gaja-v2.00 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 0.23 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=damerajee/Gaja-v2.00 |
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name: Open LLM Leaderboard |
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--- |
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# Model |
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# ๐ Gaja |
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Gaja is a Hindi/Hinglish chat model, initially trained on SarvamAI's OpenHathi model and further fine-tuned for conversational interactions. |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6487239cca30096ea9f52115/sLgskU1h2Tih_bJo0ktYR.jpeg" width="600" alt="Image"> |
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# Additional Information |
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- It outperforms Airavata, AI4Bharat's chat version, on Huggingface OpenLLM benchmark suite. |
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- It was fine-tuned on only 1k samples |
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# ๐ฌ Prompt template |
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``` |
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<|im_start|>user |
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{}<|im_end|> |
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<|im_start|>assistant |
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{}<|im_end|> |
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``` |
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# ๐ Features: |
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- Language Support: Gaja is designed to understand and generate responses in both Hindi and Hinglish, catering to a diverse range of users. |
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- Base Model: Built upon SarvamAI's OpenHathi model, Gaja inherits its foundational capabilities while being optimized for conversational tasks. |
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- Fine-tuning: Gaja has undergone fine-tuning specifically for chat-based interactions, enhancing its ability to engage in meaningful conversations with users. |
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- Experimental Platform: With its flexibility and adaptability, Gaja serves as a valuable platform for conducting experiments and exploring innovative approaches to chatbot development. |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_damerajee__Gaja-v2.00) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |46.98| |
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|AI2 Reasoning Challenge (25-Shot)|51.79| |
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|HellaSwag (10-Shot) |75.79| |
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|MMLU (5-Shot) |40.69| |
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|TruthfulQA (0-shot) |41.50| |
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|Winogrande (5-shot) |71.90| |
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|GSM8k (5-shot) | 0.23| |
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