|
--- |
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dataset_info: |
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features: |
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- name: laser_score |
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dtype: float64 |
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- name: lang1 |
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dtype: string |
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- name: text1 |
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dtype: string |
|
- name: lang2 |
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dtype: string |
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- name: text2 |
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dtype: string |
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- name: blaser_sim |
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dtype: float64 |
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splits: |
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- name: train |
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num_bytes: 2279333006.0 |
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num_examples: 9983398 |
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download_size: 1825697094 |
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dataset_size: 2279333006.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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license: odc-by |
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task_categories: |
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- translation |
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pretty_name: nllb-200-10M-sample |
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size_categories: |
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- 1M<n<10M |
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language: |
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- ak |
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- am |
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- ar |
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- awa |
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- azj |
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- bm |
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- ban |
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- be |
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- bem |
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- bn |
|
- bho |
|
- bjn |
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- bug |
|
- bg |
|
- ca |
|
- ceb |
|
- cs |
|
- cjk |
|
- ckb |
|
- crh |
|
- da |
|
- de |
|
- dik |
|
- dyu |
|
- el |
|
- en |
|
- eo |
|
- et |
|
- ee |
|
- fo |
|
- fj |
|
- fi |
|
- fon |
|
- fr |
|
- fur |
|
- ff |
|
- gaz |
|
- gd |
|
- ga |
|
- gl |
|
- gn |
|
- gu |
|
- ht |
|
- ha |
|
- he |
|
- hi |
|
- hne |
|
- hr |
|
- hu |
|
- hy |
|
- ig |
|
- ilo |
|
- id |
|
- is |
|
- it |
|
- jv |
|
- ja |
|
- kab |
|
- kac |
|
- kam |
|
- kn |
|
- ks |
|
- ks |
|
- ka |
|
- kk |
|
- kbp |
|
- kea |
|
- mn |
|
- km |
|
- ki |
|
- rw |
|
- ky |
|
- kmb |
|
- kmr |
|
- kr |
|
- kr |
|
- kg |
|
- ko |
|
- lo |
|
- lij |
|
- li |
|
- ln |
|
- lt |
|
- lmo |
|
- ltg |
|
- lb |
|
- lua |
|
- lg |
|
- luo |
|
- lus |
|
- lv |
|
- mag |
|
- mai |
|
- ml |
|
- mr |
|
- min |
|
- mk |
|
- mt |
|
- mni |
|
- mos |
|
- mi |
|
- my |
|
- nl |
|
- nb |
|
- ne |
|
- nso |
|
- nus |
|
- ny |
|
- oc |
|
- ory |
|
- pag |
|
- pa |
|
- pap |
|
- pbt |
|
- fa |
|
- plt |
|
- pl |
|
- pt |
|
- prs |
|
- qu |
|
- ro |
|
- rn |
|
- ru |
|
- sg |
|
- sa |
|
- sat |
|
- scn |
|
- shn |
|
- si |
|
- sk |
|
- sl |
|
- sm |
|
- sn |
|
- sd |
|
- so |
|
- st |
|
- es |
|
- sc |
|
- sr |
|
- ss |
|
- su |
|
- sv |
|
- sw |
|
- szl |
|
- ta |
|
- taq |
|
- tt |
|
- te |
|
- tg |
|
- tl |
|
- ti |
|
- tpi |
|
- tn |
|
- ts |
|
- tk |
|
- tum |
|
- tr |
|
- tw |
|
- tzm |
|
- ug |
|
- uk |
|
- umb |
|
- ur |
|
- uz |
|
- vec |
|
- vi |
|
- war |
|
- wo |
|
- xh |
|
- yi |
|
- yo |
|
- zh |
|
- zh |
|
- ms |
|
- zu |
|
--- |
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# Dataset Card for "nllb-200-10M-sample" |
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|
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This is a sample of nearly 10M sentence pairs from the [NLLB-200](https://arxiv.org/abs/2207.04672) |
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mined dataset [allenai/nllb](https://huggingface.co/datasets/allenai/nllb), |
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scored with the model [facebook/blaser-2.0-qe](https://huggingface.co/facebook/blaser-2.0-qe) |
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described in the [SeamlessM4T](https://arxiv.org/abs/2308.11596) paper. |
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|
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The sample is not random; instead, we just took the top `n` sentence pairs from each translation direction. |
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The number `n` was computed with the goal of upsamping the directions that contain underrepresented languages. |
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Nevertheless, the 187 languoids (language and script combinations) are not represented equally, |
|
with most languoids totaling 36K to 200K sentences. |
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Over 60% of the sentence pairs have BLASER-QE score above 3.5. |
|
|
|
This dataset can be used for fine-tuning massively multilingual translation models. |
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We suggest the following scenario: |
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- Filter the dataset by the value of `blaser_sim` (the recommended threshold is 3.0 or 3.5); |
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- Randomly swap the source/target roles in the sentence pairs during data loading; |
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- Use that data to augment the dataset while fine-tuning an NLLB-like model for a new translation direction, |
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in order to mitigate forgetting of all the other translation directions. |
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|
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The dataset is released under the terms of [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). |
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By using this, you are also bound to the respective Terms of Use and License of the original source. |
|
|
|
Citation: |
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- NLLB Team et al, *No Language Left Behind: Scaling Human-Centered Machine Translation*, Arxiv https://arxiv.org/abs/2207.04672, 2022. |
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- Seamless Communication et al, *SeamlessM4T — Massively Multilingual & Multimodal Machine Translation*, Arxiv https://arxiv.org/abs/2308.11596, 2023. |
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|
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The following language codes are supported. The mapping between languages and codes can be found in the [NLLB-200 paper](https://arxiv.org/abs/2207.04672) |
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or in the [FLORES-200 repository](https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200). |
|
``` |
|
aka_Latn amh_Ethi arb_Arab awa_Deva azj_Latn bam_Latn ban_Latn bel_Cyrl bem_Latn ben_Beng bho_Deva bjn_Latn |
|
bug_Latn bul_Cyrl cat_Latn ceb_Latn ces_Latn cjk_Latn ckb_Arab crh_Latn dan_Latn deu_Latn dik_Latn dyu_Latn |
|
ell_Grek eng_Latn epo_Latn est_Latn ewe_Latn fao_Latn fij_Latn fin_Latn fon_Latn fra_Latn fur_Latn fuv_Latn |
|
gaz_Latn gla_Latn gle_Latn glg_Latn grn_Latn guj_Gujr hat_Latn hau_Latn heb_Hebr hin_Deva hne_Deva hrv_Latn |
|
hun_Latn hye_Armn ibo_Latn ilo_Latn ind_Latn isl_Latn ita_Latn jav_Latn jpn_Jpan kab_Latn kac_Latn kam_Latn |
|
kan_Knda kas_Arab kas_Deva kat_Geor kaz_Cyrl kbp_Latn kea_Latn khk_Cyrl khm_Khmr kik_Latn kin_Latn kir_Cyrl |
|
kmb_Latn kmr_Latn knc_Arab knc_Latn kon_Latn kor_Hang lao_Laoo lij_Latn lim_Latn lin_Latn lit_Latn lmo_Latn |
|
ltg_Latn ltz_Latn lua_Latn lug_Latn luo_Latn lus_Latn lvs_Latn mag_Deva mai_Deva mal_Mlym mar_Deva min_Latn |
|
mkd_Cyrl mlt_Latn mni_Beng mos_Latn mri_Latn mya_Mymr nld_Latn nob_Latn npi_Deva nso_Latn nus_Latn nya_Latn |
|
oci_Latn ory_Orya pag_Latn pan_Guru pap_Latn pbt_Arab pes_Arab plt_Latn pol_Latn por_Latn prs_Arab quy_Latn |
|
ron_Latn run_Latn rus_Cyrl sag_Latn san_Deva sat_Beng scn_Latn shn_Mymr sin_Sinh slk_Latn slv_Latn smo_Latn |
|
sna_Latn snd_Arab som_Latn sot_Latn spa_Latn srd_Latn srp_Cyrl ssw_Latn sun_Latn swe_Latn swh_Latn szl_Latn |
|
tam_Taml taq_Latn tat_Cyrl tel_Telu tgk_Cyrl tgl_Latn tir_Ethi tpi_Latn tsn_Latn tso_Latn tuk_Latn tum_Latn |
|
tur_Latn twi_Latn tzm_Tfng uig_Arab ukr_Cyrl umb_Latn urd_Arab uzn_Latn vec_Latn vie_Latn war_Latn wol_Latn |
|
xho_Latn ydd_Hebr yor_Latn zho_Hans zho_Hant zsm_Latn zul_Latn |
|
``` |
|
|