Documentation changes (#450)

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 <https://huggingface.co/models>`__.
         * ``num_outputs``: The number of classes.
-
+    * - `~renate.benchmark.models.l2p.LearningToPromptTransformer`
+      - `Learning to Prompt Transformer <https://arxiv.org/abs/2112.08654>`_. Supports both text and vision transformers.
+      - * ``pretrained_model_name_or_path``: Hugging Face `transformer ID <https://huggingface.co/models>`__.
+        * ``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 <https://huggingface.co/datasets>`__ 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 <https://huggingface.co/datasets/rotten_tomatoes>`__ example.
       - Please refer to `the official documentation <https://huggingface.co/datasets>`__.
+    * - 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: