Results for “torchmetrics”
17 skills
qhjqhj00 Recall
Computes the Recall metric using torchmetrics, including configuration for binary, multiclass, and multilabel tasks.
3
qhjqhj00 Logauc
Computes the LogAUC metric using the torchmetrics implementation for binary, multiclass, or multilabel classification tasks.
3
qhjqhj00 F1score
Compute the F1Score metric using torchmetrics when predictions and ground-truth labels are available.
3
qhjqhj00 Roc
Computes the Receiver Operating Characteristic (ROC) metric using torchmetrics, supporting binary, multiclass, and multilabel tasks.
3
More results
qhjqhj00 R2score
Computes the R2Score metric using torchmetrics, handling single and multi-output predictions with options for adjusted and variance-weighted scores.
3
qhjqhj00 Squad
Computes the SQuAD metric using torchmetrics, given predictions and ground truth. Use when evaluating question-answering outputs with exact match and F1 scores.
3
qhjqhj00 Auroc
Computes the AUROC metric using torchmetrics, handling binary, multiclass, and multilabel tasks with configurable thresholds and averaging.
3
qhjqhj00 Infolm
Computes the InfoLM metric from torchmetrics for evaluating text generation against ground truth, with configurable information measures and sentence-level scoring.
3
qhjqhj00 Eer
Compute the Equal Error Rate (EER) metric using torchmetrics for binary, multiclass, or multilabel classification tasks, with reference signatures and usage examples.
3
qhjqhj00 Theilsu
Computes Theil's U (uncertainty coefficient) between predictions and ground truth using the torchmetrics implementation, handling categorical data and NaN strategies.
3
neuralblitz Pytorch
Provides guidance on using PyTorch for deep learning, covering tensors, autograd, nn.Module, DataLoaders, and best practices.
1
k-dense-ai Torchdrug
Build and train graph neural networks for drug discovery, protein modeling, and molecular science using PyTorch-native tools.
30.2k · bundle
orchestra-research Tensorboard
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance using TensorBoard.
10.4k · bundle
orchestra-research Pytorch Lightning
Organizes PyTorch code with a Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks, and minimal boilerplate. Scales from laptop to supercomputer with the same code.
10.4k · bundle
orchestra-research Torchforge Rl Training
Train reinforcement learning models using torchforge, Meta's PyTorch-native RL library for scalable, algorithm-focused experimentation with GRPO, DAPO, and custom loss functions.
10.4k · bundle
qhjqhj00 Tctb
Evaluates the throughput and resource allocation efficiency of RIS-aided mobile edge computing systems by measuring the total computation task bits successfully completed under varying network conditions.
3
nvidia Tao Train Rtdetr
Train, evaluate, distill, quantize, export, and run inference for RT-DETR object detection models using NVIDIA TAO.
2.2k · bundle