Add a short description and the fine-tuning hyperparameters

README.md

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