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Team |
Task |
Date/Time |
DataID |
AMFM |
Method
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Other Resources
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System Description |
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1 | SRPOL | INDIC21en-gu | 2021/05/04 15:17:54 | 6233 | - | - | - | - | - | - | 0.821221 | - | - | - | NMT | No | Ensemble of one-to-many on all data. Pretrained on BT, finetuned on PMI |
2 | IIIT-H | INDIC21en-gu | 2021/05/03 18:07:25 | 6006 | - | - | - | - | - | - | 0.820127 | - | - | - | NMT | No | MNMT system (En-XX) trained via exploiting lexical similarity on PMI+CVIT parallel corpus, then improved using back translation on PMI monolingual data followed by fine tuning. |
3 | SRPOL | INDIC21en-gu | 2021/05/04 16:24:38 | 6259 | - | - | - | - | - | - | 0.819923 | - | - | - | NMT | No | One-to-many on all data. Pretrained on BT, finetuned on PMI |
4 | CFILT | INDIC21en-gu | 2021/05/04 00:58:22 | 6042 | - | - | - | - | - | - | 0.817681 | - | - | - | NMT | No | Multilingual(One-to-Many(En-XX)) NMT model based on Transformer with shared encoder and decoder. |
5 | mcairt | INDIC21en-gu | 2021/05/03 17:57:20 | 6003 | - | - | - | - | - | - | 0.816739 | - | - | - | NMT | No | multilingual model(one to many model) trained on all WAT 2021 data by using base transformer. |
6 | SRPOL | INDIC21en-gu | 2021/04/21 19:17:29 | 5317 | - | - | - | - | - | - | 0.816592 | - | - | - | NMT | No | Base transformer on all WAT21 data |
7 | sakura | INDIC21en-gu | 2021/05/04 04:06:30 | 6151 | - | - | - | - | - | - | 0.813350 | - | - | - | NMT | No | Pre-training multilingual mBART one2many model with training corpus followed by finetuning on PMI Parallel.
|
8 | NICT-5 | INDIC21en-gu | 2021/04/22 11:51:00 | 5350 | - | - | - | - | - | - | 0.811717 | - | - | - | NMT | No | MBART+MNMT. Beam 4. |
9 | sakura | INDIC21en-gu | 2021/05/01 11:25:02 | 5883 | - | - | - | - | - | - | 0.810246 | - | - | - | NMT | No | Fine-tuning of multilingual mBART one2many model with training corpus.
|
10 | coastal | INDIC21en-gu | 2021/05/04 01:36:35 | 6078 | - | - | - | - | - | - | 0.809795 | - | - | - | NMT | No | seq2seq model trained on all WAT2021 data |
11 | IITP-MT | INDIC21en-gu | 2021/05/04 17:41:58 | 6281 | - | - | - | - | - | - | 0.808824 | - | - | - | NMT | No | One-to-Many model trained on all training data with base Transformer. All indic language data is romanized. Model fine-tuned on BT PMI monolingual corpus. |
12 | NICT-5 | INDIC21en-gu | 2021/04/21 15:41:07 | 5275 | - | - | - | - | - | - | 0.801466 | - | - | - | NMT | No | Pretrain MBART on IndicCorp and FT on bilingual PMI data. Beam search. Model is bilingual. |
13 | ORGANIZER | INDIC21en-gu | 2021/04/08 17:20:07 | 4790 | - | - | - | - | - | - | 0.757069 | - | - | - | NMT | No | Bilingual baseline trained on PMI data. Transformer base. LR=10-3 |
14 | gaurvar | INDIC21en-gu | 2021/05/01 19:28:04 | 5927 | - | - | - | - | - | - | 0.645669 | - | - | - | NMT | No | Multi Task Multi Lingual T5 trained for Multiple Indic Languages |
15 | gaurvar | INDIC21en-gu | 2021/04/25 19:56:35 | 5580 | - | - | - | - | - | - | 0.628529 | - | - | - | NMT | No | Multi Task Multi Lingual T5 trained for Multiple Indic Languages |
16 | NICT-5 | INDIC21en-gu | 2021/06/25 11:35:46 | 6484 | - | - | - | - | - | - | 0.000000 | - | - | - | NMT | No | Using PMI and PIB data for fine-tuning on a mbart model trained for over 5 epochs. MNMT model. |