Update files from the datasets library (from 1.6.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.6.0

README.md

@@ -10,7 +10,7 @@ licenses:
 multilinguality:
 - monolingual
 size_categories:
-- n<1K
+- 100K<n<1M
 source_datasets:
 - extended|other-Switchboard-1 Telephone Speech Corpus, Release 2
 task_categories:
@@ -67,11 +67,13 @@ conversations and their participants.
 
 | Model           | Accuracy  |  Paper / Source | Code |
 | ------------- | :-----:| --- | --- |
+| H-Seq2seq (Colombo et al., 2020) | 85.0 | [Guiding attention in Sequence-to-sequence models for Dialogue Act prediction](https://ojs.aaai.org/index.php/AAAI/article/view/6259/6115)
 | SGNN (Ravi et al., 2018) | 83.1 | [Self-Governing Neural Networks for On-Device Short Text Classification](https://www.aclweb.org/anthology/D18-1105.pdf)
 | CASA (Raheja et al., 2019) | 82.9 | [Dialogue Act Classification with Context-Aware Self-Attention](https://www.aclweb.org/anthology/N19-1373.pdf)
 | DAH-CRF (Li et al., 2019) | 82.3 | [A Dual-Attention Hierarchical Recurrent Neural Network for Dialogue Act Classification](https://www.aclweb.org/anthology/K19-1036.pdf)
-| ALDMN (Wan et al., 2018) | 81.5 | [Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training](https://arxiv.org/pdf/1811.05021.pdf)
-| CRF-ASN (Chen et al., 2018) | 81.3 | [Dialogue Act Recognition via CRF-Attentive Structured Network](https://arxiv.org/abs/1711.05568) | |
+| ALDMN (Wan et al., 2018) | 81.5 | [Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training](https://arxiv.org/pdf/1811.05021.pdf) 
+| CRF-ASN (Chen et al., 2018) | 81.3 | [Dialogue Act Recognition via CRF-Attentive Structured Network](https://arxiv.org/abs/1711.05568)
+| Pretrained H-Transformer (Chapuis et al., 2020) |  79.3 | [Hierarchical Pre-training for Sequence Labelling in Spoken Dialog] (https://www.aclweb.org/anthology/2020.findings-emnlp.239)
 | Bi-LSTM-CRF (Kumar et al., 2017) | 79.2 | [Dialogue Act Sequence Labeling using Hierarchical encoder with CRF](https://arxiv.org/abs/1709.04250) | [Link](https://github.com/YanWenqiang/HBLSTM-CRF) |
 | RNN with 3 utterances in context (Bothe et al., 2018) | 77.34 | [A Context-based Approach for Dialogue Act Recognition using Simple Recurrent Neural Networks](https://arxiv.org/abs/1805.06280) | |
 
@@ -269,4 +271,4 @@ This work is licensed under a [Creative Commons Attribution-NonCommercial-ShareA
 
 ### Contributions
 
-Thanks to [@gmihaila](https://github.com/gmihaila) for adding this dataset.
+Thanks to [@gmihaila](https://github.com/gmihaila) for adding this dataset.

swda.py

@@ -22,7 +22,6 @@ This script is a modified version of the original swda.py from https://github.co
 the original corpus repo. Modifications are made to accommodate the HuggingFace Dataset project format.
 """
 
-from __future__ import absolute_import, division, print_function
 
 import csv
 import datetime