Plot scaling laws of our baseline models

For our three baselines on different datasets (OSCAR, C4, The Pile), we would like to plot scaling laws and retrieve their coefficients. Specifically, we are looking to reproduce Figure 1 of [Scaling Laws for Neural Language Models](https://arxiv.org/abs/2001.08361 ).

The TensorBoard data for the baseline runs can be retrieved on the [Big Science space](https://huggingface.co/bigscience) on HuggingFace: it's the `tr3` runs with `tensorboard` in their name. The naming scheme (`tr3b`, `tr3c`, etc.) is explained [here](https://github.com/bigscience-workshop/bigscience/tree/master/train/tr3-1B3-baseline).
For C4, we have a XL, L, and M model (`tr3`, `tr3c`, `tr3c`) with short warm-up. For OSCAR and The Pile, we have an XL, L, M, and S model (`tr3d`, `tr3g`, `tr3h`, `tr3i` and `tr3`, `tr3j`, `tr3k`, `tr3l`). For OSCAR, we can should also add the 13B run to see if the fits hold (that's `tr1-13B`).