Adding Evaluation Results
#6
by
leaderboard-pr-bot
- opened
README.md
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---
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license: apache-2.0
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language:
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- ar
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- he
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- et
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- fi
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- hu
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pipeline_tag: text-generation
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tags:
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- multilingual
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- PyTorch
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datasets:
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- mc4
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- wikipedia
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---
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# Multilingual GPT model
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The model was trained with sequence length 512 using Megatron and Deepspeed libs by [SberDevices](https://sberdevices.ru/) team on a dataset of 600 GB of texts in 61 languages. The model has seen 440 billion BPE tokens in total.
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Total training time was around 14 days on 256 Nvidia V100 GPUs.
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---
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language:
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- ar
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- he
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- et
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- fi
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- hu
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license: apache-2.0
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tags:
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- multilingual
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- PyTorch
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datasets:
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- mc4
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- wikipedia
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pipeline_tag: text-generation
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thumbnail: https://github.com/sberbank-ai/mgpt
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model-index:
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- name: mGPT
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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: 23.81
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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=ai-forever/mGPT
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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: 26.37
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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=ai-forever/mGPT
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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: 25.17
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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=ai-forever/mGPT
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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: 39.62
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ai-forever/mGPT
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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: 50.67
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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=ai-forever/mGPT
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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: 0.0
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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=ai-forever/mGPT
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name: Open LLM Leaderboard
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---
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# Multilingual GPT model
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The model was trained with sequence length 512 using Megatron and Deepspeed libs by [SberDevices](https://sberdevices.ru/) team on a dataset of 600 GB of texts in 61 languages. The model has seen 440 billion BPE tokens in total.
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Total training time was around 14 days on 256 Nvidia V100 GPUs.
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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_ai-forever__mGPT)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |27.61|
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|AI2 Reasoning Challenge (25-Shot)|23.81|
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|HellaSwag (10-Shot) |26.37|
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|MMLU (5-Shot) |25.17|
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|TruthfulQA (0-shot) |39.62|
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|Winogrande (5-shot) |50.67|
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|GSM8k (5-shot) | 0.00|
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