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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# mistral-1L-tiny
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This model is trained on the roneneldan/TinyStories dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6868
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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### Training results
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### Framework versions
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value: 0.5792084706530948
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# mistral-1L-tiny
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A tiny single-layer 35.1M parameter Mistral model, with a hidden size of 512, and an MLP intermediate size of 1024.
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This model is trained on the roneneldan/TinyStories dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6868
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## Model description
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This work is inspired by the 21M parameter one-layer GPT-Neo of the [Tiny Stories paper](https://arxiv.org/abs/2305.07759).
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Results reproduced to acquire high-frequency checkpoints for further analysis.
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## Intended uses & limitations
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Analysis of feature dynamics and emergence in real-world language models.
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## Training procedure
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Trained for 90171 steps, corresponding to ~2 hours on a single H100.
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### Training hyperparameters
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The following hyperparameters were used during training:
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### Training results
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Quite consistent English text generation.
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### Framework versions
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