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--- |
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license: cc0-1.0 |
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datasets: |
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- JeanKaddour/minipile |
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language: |
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- en |
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library_name: transformers |
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--- |
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GPT-NeoX trained on MiniPile, for a baseline to compare my MANN models against. Uses [NeelNanda/gpt-neox-tokenizer-digits](https://huggingface.co/NeelNanda/gpt-neox-tokenizer-digits) for tokenization. |
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The exact model configuration is as follows: |
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``` |
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cfg = GPTNeoXConfig( |
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vocab_size = len(tokenizer), |
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hidden_size = 768, |
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intermediate_size = 768*4, |
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num_hidden_layers = 12, |
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num_attention_heads = 12, |
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tie_word_embeddings = True, |
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hidden_act = "gelu_new", |
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tokenizer = "NeelNanda/gpt-neox-tokenizer-digits" |
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) |
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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_euclaise__gpt-neox-122m-minipile-digits) |
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| Metric | Value | |
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|-----------------------|---------------------------| |
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| Avg. | 25.1 | |
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| ARC (25-shot) | 20.73 | |
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| HellaSwag (10-shot) | 27.03 | |
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| MMLU (5-shot) | 25.31 | |
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| TruthfulQA (0-shot) | 49.19 | |
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| Winogrande (5-shot) | 52.33 | |
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| GSM8K (5-shot) | 0.0 | |
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| DROP (3-shot) | 1.09 | |
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