leaderboard-pr-bot
commited on
Adding Evaluation Results
Browse filesThis is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr
The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.
If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions
README.md
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---
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license: llama2
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language:
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- hi
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---
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This repository is the first model in the OpenHathi series of models that will be released by Sarvam AI. This is a 7B parameter, based on Llama2, trained on Hindi, English, and Hinglish. More details about the model, its training procedure, and evaluations can be found [here](https://www.sarvam.ai/blog/announcing-openhathi-series).
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@@ -21,4 +124,17 @@ inputs = tokenizer(prompt, return_tensors="pt")
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# Generate
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generate_ids = model.generate(inputs.input_ids, max_length=30)
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tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
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```
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---
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language:
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- hi
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license: llama2
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model-index:
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- name: OpenHathi-7B-Hi-v0.1-Base
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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: 49.49
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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=sarvamai/OpenHathi-7B-Hi-v0.1-Base
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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: 74.34
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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=sarvamai/OpenHathi-7B-Hi-v0.1-Base
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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: 41.38
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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=sarvamai/OpenHathi-7B-Hi-v0.1-Base
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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: 37.46
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sarvamai/OpenHathi-7B-Hi-v0.1-Base
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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: 71.27
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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=sarvamai/OpenHathi-7B-Hi-v0.1-Base
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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: 5.91
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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=sarvamai/OpenHathi-7B-Hi-v0.1-Base
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name: Open LLM Leaderboard
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---
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This repository is the first model in the OpenHathi series of models that will be released by Sarvam AI. This is a 7B parameter, based on Llama2, trained on Hindi, English, and Hinglish. More details about the model, its training procedure, and evaluations can be found [here](https://www.sarvam.ai/blog/announcing-openhathi-series).
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# Generate
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generate_ids = model.generate(inputs.input_ids, max_length=30)
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tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
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```
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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_sarvamai__OpenHathi-7B-Hi-v0.1-Base)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |46.64|
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|AI2 Reasoning Challenge (25-Shot)|49.49|
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|HellaSwag (10-Shot) |74.34|
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|MMLU (5-Shot) |41.38|
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|TruthfulQA (0-shot) |37.46|
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|Winogrande (5-shot) |71.27|
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|GSM8k (5-shot) | 5.91|
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