Add RoBERTa-based GPT-2 Output Detector from OpenAI

converted from https://github.com/openai/gpt-2-output-dataset/tree/master/detector

Co-Authored-By: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
Co-Authored-By: Jong Wook Kim <jongwook@nyu.edu>
Co-Authored-By: Jeff Wu <wuthefwasthat@gmail.com>
This commit is contained in:
Julien Chaumond
2019-11-06 16:26:31 -05:00
parent 2f3a421018
commit 1c542df7e5
4 changed files with 18 additions and 0 deletions

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@@ -127,6 +127,14 @@ Here is the full list of the currently provided pretrained models together with
| | ``roberta-large-mnli`` | | 24-layer, 1024-hidden, 16-heads, 355M parameters |
| | | | ``roberta-large`` fine-tuned on `MNLI <http://www.nyu.edu/projects/bowman/multinli/>`__. |
| | | (see `details <https://github.com/pytorch/fairseq/tree/master/examples/roberta>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``roberta-base-openai-detector`` | | 12-layer, 768-hidden, 12-heads, 125M parameters |
| | | | ``roberta-base`` fine-tuned by OpenAI on the outputs of the 1.5B-parameter GPT-2 model. |
| | | (see `details <https://github.com/openai/gpt-2-output-dataset/tree/master/detector>`__) |
| +------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| | ``roberta-large-openai-detector`` | | 24-layer, 1024-hidden, 16-heads, 355M parameters |
| | | | ``roberta-large`` fine-tuned by OpenAI on the outputs of the 1.5B-parameter GPT-2 model. |
| | | (see `details <https://github.com/openai/gpt-2-output-dataset/tree/master/detector>`__) |
+-------------------+------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------+
| DistilBERT | ``distilbert-base-uncased`` | | 6-layer, 768-hidden, 12-heads, 66M parameters |
| | | | The DistilBERT model distilled from the BERT model `bert-base-uncased` checkpoint |