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license: unknown |
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language: |
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- en |
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# Baby Llama |
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Our submission to the `strict-small` track of the [BabyLM challenge](https://babylm.github.io/index.html). |
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Baby Llama is a 58-million-parameter model, distilled from an ensemble consisting of LLaMA-360M and GPT2-705M, both trained on the `babylm_10M` dataset. |
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See the associated paper (arXiv number **TBA**) for a detailed discussion of the training procedure and of the model performance. |
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### Hyperparameters for the tasks requiring fine-tuning |
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When evaluating the model on the [tasks that require fine-tuning](https://github.com/babylm/evaluation-pipeline/tree/main#fine-tuning), |
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we noticed that the [default hyperparameters](https://github.com/babylm/evaluation-pipeline/tree/main#hyperparameters) |
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suggested by the BabyLM organizers lead to severe overfitting in a number of tasks. |
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To avoid this issue, we have re-tuned those hyperparameters. |
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The sets of hyperparameters selected for each task are listed in the table below. |
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A star (*) indicates that the early-stopping criterion was triggered before the specified number of epochs was reached. |
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| Task | Initial learning rate | Batch size | Maximum epochs | Patience | Evaluate every (steps) | Random seed | |
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| ---- | ------------- | ---------- | -------- | -------- | ---------- | ---- | |
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| CoLA | | | | | | | |
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| SST-2 | | | | | | | |
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| MRPC | | | | | | | |
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| QQP | | | | | | | |
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| MNLI | | | | | | | |
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| MNLI-mm | | | | | | | |
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| QNLI | | | | | | | |
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| RTE | 5e-5 | 64 | 6 | 10 | 200 | 12 | |
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| BoolQ | 3e-4 | 16 | 10* | 10 | 10 | 12 | |
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| MultiRC | 1e-4 | 64 | 7 | 10 | 1000 | 42 | |
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| WSC | 5e-7 | 1 | 10 | 1000 | 2000 | 12 | |
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| CR (Control) | | | | | | | |
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| LC (Control) | | | | | | | |
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| MV (Control) | | | | | | | |
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| RP (Control) | | | | | | | |
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| SC (Control) | | | | | | | |
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| CR\_LC | | | | | | | |
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| CR\_RTP | | | | | | | |
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| MV\_LC | | | | | | | |
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| MV\_RTP | | | | | | | |
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| SC\_LC | | | | | | | |
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| SC\_RP | | | | | | | |
