From 2e1efce4f4d8a4125cab284955c447a7ffa0ef82 Mon Sep 17 00:00:00 2001 From: Prabhu Teja Date: Mon, 9 Oct 2023 13:28:13 +0200 Subject: [PATCH] Documentation changes (#450) --- doc/benchmarking/renate_benchmarks.rst | 17 ++++++++++++++++- 1 file changed, 16 insertions(+), 1 deletion(-) diff --git a/doc/benchmarking/renate_benchmarks.rst b/doc/benchmarking/renate_benchmarks.rst index f914eb84..3bb602e6 100644 --- a/doc/benchmarking/renate_benchmarks.rst +++ b/doc/benchmarking/renate_benchmarks.rst @@ -97,7 +97,14 @@ The full list of models and model names including a short description is provide - Wrapper around Hugging Face transformers. - * ``pretrained_model_name_or_path``: Hugging Face `transformer ID `__. * ``num_outputs``: The number of classes. - + * - `~renate.benchmark.models.l2p.LearningToPromptTransformer` + - `Learning to Prompt Transformer `_. Supports both text and vision transformers. + - * ``pretrained_model_name_or_path``: Hugging Face `transformer ID `__. + * ``num_outputs``: The number of classes. + * ``pool_size``: Total number of prompts in the prompt pool. + * ``pool_selection_size``: Number of prompts to select for each input from the pool. + * ``prompt_size``: Number of input tokens each prompt is equivalent to. + * ``prompt_key_dim``: Dimenensionality of the features used for prompt matching. .. _benchmarking-renate-benchmarks-datasets: @@ -173,6 +180,14 @@ The following table contains the list of supported datasets. - multiple - Any `Hugging Face dataset `__ can be used. Just prepend the prefix ``hfd-``, e.g., ``hfd-rotten_tomatoes``. Select input and target columns via ``config_space``, e.g., add ``"input_column": "text", "target_column": "label"`` for the `rotten_tomatoes `__ example. - Please refer to `the official documentation `__. + * - CDDB + - Image Classification: deepfake detection + - 2 classes, 5 domains, each generated using image generation techniques: GauGAN, BigGAN, WildDeepfake, WhichFaceReal, SAN respectively from HARD evaluation scenario. Numbers vary across domains. + - Li, Chuqiao, et al. A continual deepfake detection benchmark: Dataset, methods, and essentials. IEEE/CVF Winter Conference on Applications of Computer Vision. 2023. + * - Core50 + - Image Classfication + - 50 classes, 8 (0-7) domains for training, a single test set for evaluation. + - Vincenzo Lomonaco and Davide Maltoni: CORe50: a new Dataset and Benchmark for continual Object Recognition. 1st Annual Conference on Robot Learning, PMLR 78:17-26, 2017. .. _benchmarking-renate-benchmarks-scenarios: