From ca9dd7cff6373ae73a7f50ef7721320a305c638c Mon Sep 17 00:00:00 2001 From: Peter Dudfield <34686298+peterdudfield@users.noreply.github.com> Date: Tue, 14 May 2024 16:28:15 +0200 Subject: [PATCH] N samples experiments (#188) * update experiments * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add 400 experiment * update plot * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- experiments/analysis.py | 3 ++ .../india/004_n_training_samples/log-plot.py | 14 +++++ .../004_n_training_samples/mae_samples.png | Bin 0 -> 76959 bytes .../india/004_n_training_samples/mae_step.png | Bin 0 -> 325416 bytes .../india/004_n_training_samples/readme.md | 48 ++++++++++++++++++ 5 files changed, 65 insertions(+) create mode 100644 experiments/india/004_n_training_samples/log-plot.py create mode 100644 experiments/india/004_n_training_samples/mae_samples.png create mode 100644 experiments/india/004_n_training_samples/mae_step.png create mode 100644 experiments/india/004_n_training_samples/readme.md diff --git a/experiments/analysis.py b/experiments/analysis.py index 28a1ea6a..6212a881 100644 --- a/experiments/analysis.py +++ b/experiments/analysis.py @@ -72,6 +72,9 @@ def main(runs: list[str], run_names: list[str]) -> None: group_string += f" {df.iloc[group_idx].mean()*100.:0.3f} |" print(group_string) + for idx, df in enumerate(dfs): + print(f"{run_names[idx]}: {df.mean()*100:0.3f}") + # Plot the error on per timestep, and grouped timesteps plt.figure() for idx, df in enumerate(dfs): diff --git a/experiments/india/004_n_training_samples/log-plot.py b/experiments/india/004_n_training_samples/log-plot.py new file mode 100644 index 00000000..e876384a --- /dev/null +++ b/experiments/india/004_n_training_samples/log-plot.py @@ -0,0 +1,14 @@ +""" Small script to make MAE vs number of batches plot""" + +import pandas as df +import plotly.graph_objects as go + +data = [[100, 7.779], [300, 7.441], [1000, 7.181], [3000, 7.180], [6711, 7.151]] +df = df.DataFrame(data, columns=["n_samples", "MAE [%]"]) + +fig = go.Figure() +fig.add_trace(go.Scatter(x=df["n_samples"], y=df["MAE [%]"], mode="lines+markers")) +fig.update_layout(title="MAE % for N samples", xaxis_title="N Samples", yaxis_title="MAE %") +# change to log log +fig.update_xaxes(type="log") +fig.show(renderer="browser") diff --git a/experiments/india/004_n_training_samples/mae_samples.png b/experiments/india/004_n_training_samples/mae_samples.png new file mode 100644 index 0000000000000000000000000000000000000000..d2bbd907c3e7b21291b4099ceeb05cc95a87f3f0 GIT binary patch literal 76959 zcmeFZWmr|+_CAb=iXaMtprEAEDcv9_(%lVG5?i`U1hyhAAuZkAwUJc1H;sUFcf)`3 z#5w18_I^ITU*79*U0iI|+B4RebBuA1dyKh0%E^dfVGv@VprBxhzZO+MLAgnWf^t0# 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100644 index 00000000..0d2ce2ef --- /dev/null +++ b/experiments/india/004_n_training_samples/readme.md @@ -0,0 +1,48 @@ +# N samples experiments + +Kicked off an experiment that uses N samples +This is done by adding `limit_train_batches` to the `trainer/default.yaml`. + +I checked that when limiting the batches, the same batches are shown to model for each epoch. + +## Experiments + +Original is 6711 batches + +- 100: 3p6scx2r +- 300: am46tno1 +- 1000: u04xlb6p +- 3000: p11lhreo + +## Results + +Overall + +| Experiment | MAE % | +|------------|-------| +| 100 | 7.779 | +| 300 | 7.441 | +| 1000 | 7.181 | +| 3000 | 7.180 | +| 6711 | 7.151 | + +Results by timestamps + + +| Timestep | 100 MAE % | 300 MAE % | 1000 MAE % | 3000 MAE % | 6711 MAE % | +| --- | --- | --- | --- | --- | --- | +| 0-0 minutes | 7.985 | 7.453 | 7.155 | 5.553 | 5.920 | +| 15-15 minutes | 7.953 | 7.055 | 6.923 | 5.453 | 5.809 | +| 30-45 minutes | 8.043 | 7.172 | 6.907 | 5.764 | 5.742 | +| 45-60 minutes | 7.850 | 7.070 | 6.790 | 5.815 | 5.698 | +| 60-120 minutes | 7.698 | 6.809 | 6.597 | 5.890 | 5.816 | +| 120-240 minutes | 7.355 | 6.629 | 6.495 | 6.221 | 6.080 | +| 240-360 minutes | 7.230 | 6.729 | 6.559 | 6.541 | 6.375 | +| 360-480 minutes | 7.415 | 6.997 | 6.770 | 6.855 | 6.638 | +| 480-720 minutes | 7.258 | 7.037 | 6.668 | 6.876 | 6.747 | +| 720-1440 minutes | 7.659 | 7.362 | 7.038 | 7.142 | 7.207 | +| 1440-2880 minutes | 8.027 | 7.745 | 7.518 | 7.535 | 7.507 | + +![](mae_step.png "mae_steps") + +![](mae_samples.png "mae_samples")