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license: cc-by-nc-sa-4.0 |
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pipeline_tag: fill-mask |
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language: en |
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datasets: |
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- OpenSubtitles |
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library_name: transformers |
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--- |
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## Model description |
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This model is based on [An Exploration of Hierarchical Attention Transformers for Efficient Long Document Classification](https://arxiv.org/abs/2210.05529). Ilias Chalkidis, Xiang Dai, Manos Fergadiotis, Prodromos Malakasiotis, and Desmond Elliott. 2022. arXiv:2210.05529 (Preprint). |
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Initial weights were taken from [google/bert_uncased_L-8_H-256_A-4](https://huggingface.co/google/bert_uncased_L-8_H-256_A-4). |
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Model was additionally pretrained for 20_000 steps on 5m lines of text from english version of [OpenSubtitles](http://www.opensubtitles.org/) dataset. |
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Maximum input length is 512 tokens that is enoungh to encode dialog with few previous utterances (average sentence length per utterance in SWDA, MAPTASK, MRDA, BT_OASIS, FRAMES, AMI, DSTC3 is less than 11 tokens). |
