data
sequence | label
int64 0
1
|
---|---|
[[-0.34117645025253296,-0.34117645025253296,-0.14705884456634521,-0.14705884456634521,-0.11764699220(...TRUNCATED) | 0 |
[[-0.2183908224105835,-0.2183908224105835,-0.14942526817321777,-0.14942526817321777,-0.1494252681732(...TRUNCATED) | 1 |
[[-0.2744479775428772,-0.2744479775428772,-0.3627760410308838,-0.3627760410308838,-0.362776041030883(...TRUNCATED) | 1 |
[[-0.19266051054000854,-0.19266051054000854,-0.10703355073928833,-0.10703355073928833,-0.24159008264(...TRUNCATED) | 0 |
[[-0.12354308366775513,-0.12354308366775513,-0.23543119430541992,-0.23543119430541992,-0.21212118864(...TRUNCATED) | 1 |
[[-0.22807013988494873,-0.22807013988494873,-0.39181286096572876,-0.39181286096572876,-0.32163739204(...TRUNCATED) | 0 |
[[-0.20379143953323364,-0.20379143953323364,-0.03317534923553467,-0.03317534923553467,-0.17535537481(...TRUNCATED) | 1 |
[[-0.09192204475402832,-0.09192204475402832,-0.1309192180633545,-0.1309192180633545,-0.0194985866546(...TRUNCATED) | 0 |
[[-0.1726619005203247,-0.1726619005203247,-0.16546761989593506,-0.16546761989593506,-0.1366906166076(...TRUNCATED) | 1 |
[[-0.2686084508895874,-0.2686084508895874,-0.508090615272522,-0.508090615272522,-0.5339806079864502,(...TRUNCATED) | 0 |
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in Dataset Viewer.
The EEG Motor Movement/Imagery (MMI) Dataset preprocessed with DN3 to be used for downstream fine-tuning with BENDR.
The labels correspond to Task 4 (imagine opening and closing both fists or both feet) from experimental runs 4, 10 and 14.
Creating dataloaders
from datasets import load_dataset
from torch.utils.data import DataLoader
dataset = load_dataset("rasgaard/mmi-bendr-preprocessed")
dataset.set_format("torch")
train_loader = DataLoader(dataset["train"], batch_size=8)
val_loader = DataLoader(dataset["val"], batch_size=8)
test_loader = DataLoader(dataset["test"], batch_size=8)
batch = next(iter(train_loader))
batch["data"].shape, batch["label"].shape
>>> (torch.Size([8, 20, 1536]), torch.Size([8]))
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