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Model: finnianx/michel-micro Source: Original Platform
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README.md
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README.md
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---
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datasets:
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- HuggingFaceFW/fineweb-edu
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- HuggingFaceTB/cosmopedia
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- epfml/FineWeb2-HQ
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language:
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- en
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---
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An ultra-tiny 28 million parameter model trained on 2.6 billion tokens using a custom dataset mixture. Context length of 1024 tokens.
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| Dataset | Weight |
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|---|---|
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| `HuggingFaceFW/fineweb-edu` | 50% |
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| `epfml/FineWeb-HQ` | 30% |
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| `HuggingFaceTB/cosmopedia` (stories split) | 20% |
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The tokenizer is a basic bpe tokenizer that was trained on a smaller subset of 80_000 samples of this same data mixture with a vocab size of 8000.
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This model has not undergone any post-training.
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This base model is best suited for fine-tuning on specific tasks. On its own, it is very limited, but it is a pretty flexible foundation for applications such as toxic comment detection or sentiment analysis.
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| Benchmark | Metric | Value |
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|---|---|---|
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| ARC-Challenge | Acc | 0.1980 |
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| ARC-Challenge | Acc Norm | 0.2312 |
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| ARC-Easy | Acc | 0.4091 |
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| ARC-Easy | Acc Norm | 0.3859 |
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| BoolQ | Acc | 0.5850 |
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| HellaSwag | Acc | 0.2749 |
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| HellaSwag | Acc Norm | 0.2823 |
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| PIQA | Acc | 0.5963 |
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| PIQA | Acc Norm | 0.5762 |
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| WinoGrande | Acc | 0.4917 |
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| WikiText | Word PPL | 86.6418 |
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| WikiText | Byte PPL | 2.3034 |
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| WikiText | Bits/Byte | 1.2037 |
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| BLIMP (Avg) | Acc | 0.6975 |
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