composer.models
Models provided to Trainer must use the basic
interface specified by BaseMosaicModel.
Additionally, for convience we provide a number of extensions of BaseMosaicModel
as detailed below.
Base Models
Implements the base logic that all Transformers can build on top off. |
Image Models
Language Models
Metrics and Loss Functions
Evaluation metrics for common tasks are
in torchmetrics
and are directly compatible with BaseMosaicModel.
Additionally, we provide implementations of the following metrics and loss functions.
Torchmetric implementation to calculate validation loss |
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Drop-in replacement for torch.CrossEntropy that can handle dense labels. |
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Implements a CrossEntropyLoss metric that can be run during the validation step, and is compatible with the HF API. |
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Subclasses the LanguageCrossEntropyLoss to provide a perplexity measurement. |