readme: ---
  language:
  - all
  license: apache-2.0
  tags:
  - fleurs-lang_id
  - google/xtreme_s
  - generated_from_trainer
  datasets:
  - google/xtreme_s
  metrics:
  - accuracy
  model-index:
  - name: xtreme_s_xlsr_300m_fleurs_langid
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # xtreme_s_xlsr_300m_fleurs_langid
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the GOOGLE/XTREME_S - FLEURS.ALL dataset.
  It achieves the following results on the evaluation set:
  - Accuracy: 0.7271
  - Accuracy Af Za: 0.3865
  - Accuracy Am Et: 0.8818
  - Accuracy Ar Eg: 0.9977
  - Accuracy As In: 0.9858
  - Accuracy Ast Es: 0.8362
  - Accuracy Az Az: 0.8386
  - Accuracy Be By: 0.4085
  - Accuracy Bn In: 0.9989
  - Accuracy Bs Ba: 0.2508
  - Accuracy Ca Es: 0.6947
  - Accuracy Ceb Ph: 0.9852
  - Accuracy Cmn Hans Cn: 0.9799
  - Accuracy Cs Cz: 0.5353
  - Accuracy Cy Gb: 0.9716
  - Accuracy Da Dk: 0.6688
  - Accuracy De De: 0.7807
  - Accuracy El Gr: 0.7692
  - Accuracy En Us: 0.9815
  - Accuracy Es 419: 0.9846
  - Accuracy Et Ee: 0.5230
  - Accuracy Fa Ir: 0.8462
  - Accuracy Ff Sn: 0.2348
  - Accuracy Fi Fi: 0.9978
  - Accuracy Fil Ph: 0.9564
  - Accuracy Fr Fr: 0.9852
  - Accuracy Ga Ie: 0.8468
  - Accuracy Gl Es: 0.5016
  - Accuracy Gu In: 0.973
  - Accuracy Ha Ng: 0.9163
  - Accuracy He Il: 0.8043
  - Accuracy Hi In: 0.9354
  - Accuracy Hr Hr: 0.3654
  - Accuracy Hu Hu: 0.8044
  - Accuracy Hy Am: 0.9914
  - Accuracy Id Id: 0.9869
  - Accuracy Ig Ng: 0.9360
  - Accuracy Is Is: 0.0217
  - Accuracy It It: 0.8
  - Accuracy Ja Jp: 0.7385
  - Accuracy Jv Id: 0.5824
  - Accuracy Ka Ge: 0.8611
  - Accuracy Kam Ke: 0.4184
  - Accuracy Kea Cv: 0.8692
  - Accuracy Kk Kz: 0.8727
  - Accuracy Km Kh: 0.7030
  - Accuracy Kn In: 0.9630
  - Accuracy Ko Kr: 0.9843
  - Accuracy Ku Arab Iq: 0.9577
  - Accuracy Ky Kg: 0.8936
  - Accuracy Lb Lu: 0.8897
  - Accuracy Lg Ug: 0.9253
  - Accuracy Ln Cd: 0.9644
  - Accuracy Lo La: 0.1580
  - Accuracy Lt Lt: 0.4686
  - Accuracy Luo Ke: 0.9922
  - Accuracy Lv Lv: 0.6498
  - Accuracy Mi Nz: 0.9613
  - Accuracy Mk Mk: 0.7636
  - Accuracy Ml In: 0.6962
  - Accuracy Mn Mn: 0.8462
  - Accuracy Mr In: 0.3911
  - Accuracy Ms My: 0.3632
  - Accuracy Mt Mt: 0.6188
  - Accuracy My Mm: 0.9705
  - Accuracy Nb No: 0.6891
  - Accuracy Ne Np: 0.8994
  - Accuracy Nl Nl: 0.9093
  - Accuracy Nso Za: 0.8873
  - Accuracy Ny Mw: 0.4691
  - Accuracy Oci Fr: 0.1533
  - Accuracy Om Et: 0.9512
  - Accuracy Or In: 0.5447
  - Accuracy Pa In: 0.8153
  - Accuracy Pl Pl: 0.7757
  - Accuracy Ps Af: 0.8105
  - Accuracy Pt Br: 0.7715
  - Accuracy Ro Ro: 0.4122
  - Accuracy Ru Ru: 0.9794
  - Accuracy Rup Bg: 0.9468
  - Accuracy Sd Arab In: 0.5245
  - Accuracy Sk Sk: 0.8624
  - Accuracy Sl Si: 0.0300
  - Accuracy Sn Zw: 0.8843
  - Accuracy So So: 0.8803
  - Accuracy Sr Rs: 0.0257
  - Accuracy Sv Se: 0.0145
  - Accuracy Sw Ke: 0.9199
  - Accuracy Ta In: 0.9526
  - Accuracy Te In: 0.9788
  - Accuracy Tg Tj: 0.9883
  - Accuracy Th Th: 0.9912
  - Accuracy Tr Tr: 0.7887
  - Accuracy Uk Ua: 0.0627
  - Accuracy Umb Ao: 0.7863
  - Accuracy Ur Pk: 0.0134
  - Accuracy Uz Uz: 0.4014
  - Accuracy Vi Vn: 0.7246
  - Accuracy Wo Sn: 0.4555
  - Accuracy Xh Za: 1.0
  - Accuracy Yo Ng: 0.7353
  - Accuracy Yue Hant Hk: 0.7985
  - Accuracy Zu Za: 0.4696
  - Loss: 1.3789
  - Loss Af Za: 2.6778
  - Loss Am Et: 0.4615
  - Loss Ar Eg: 0.0149
  - Loss As In: 0.0764
  - Loss Ast Es: 0.4560
  - Loss Az Az: 0.5677
  - Loss Be By: 1.9231
  - Loss Bn In: 0.0024
  - Loss Bs Ba: 2.4954
  - Loss Ca Es: 1.2632
  - Loss Ceb Ph: 0.0426
  - Loss Cmn Hans Cn: 0.0650
  - Loss Cs Cz: 1.9334
  - Loss Cy Gb: 0.1274
  - Loss Da Dk: 1.4990
  - Loss De De: 0.8820
  - Loss El Gr: 0.9839
  - Loss En Us: 0.0827
  - Loss Es 419: 0.0516
  - Loss Et Ee: 1.9264
  - Loss Fa Ir: 0.6520
  - Loss Ff Sn: 5.4283
  - Loss Fi Fi: 0.0109
  - Loss Fil Ph: 0.1706
  - Loss Fr Fr: 0.0591
  - Loss Ga Ie: 0.5174
  - Loss Gl Es: 1.2657
  - Loss Gu In: 0.0850
  - Loss Ha Ng: 0.3234
  - Loss He Il: 0.8299
  - Loss Hi In: 0.4190
  - Loss Hr Hr: 2.9754
  - Loss Hu Hu: 0.8345
  - Loss Hy Am: 0.0329
  - Loss Id Id: 0.0529
  - Loss Ig Ng: 0.2523
  - Loss Is Is: 6.5153
  - Loss It It: 0.8113
  - Loss Ja Jp: 1.3968
  - Loss Jv Id: 2.0009
  - Loss Ka Ge: 0.6162
  - Loss Kam Ke: 2.2192
  - Loss Kea Cv: 0.5567
  - Loss Kk Kz: 0.5592
  - Loss Km Kh: 1.7358
  - Loss Kn In: 0.1063
  - Loss Ko Kr: 0.1519
  - Loss Ku Arab Iq: 0.2075
  - Loss Ky Kg: 0.4639
  - Loss Lb Lu: 0.4454
  - Loss Lg Ug: 0.3764
  - Loss Ln Cd: 0.1844
  - Loss Lo La: 3.8051
  - Loss Lt Lt: 2.5054
  - Loss Luo Ke: 0.0479
  - Loss Lv Lv: 1.3713
  - Loss Mi Nz: 0.1390
  - Loss Mk Mk: 0.7952
  - Loss Ml In: 1.2999
  - Loss Mn Mn: 0.7621
  - Loss Mr In: 3.7056
  - Loss Ms My: 3.0192
  - Loss Mt Mt: 1.5520
  - Loss My Mm: 0.1514
  - Loss Nb No: 1.1194
  - Loss Ne Np: 0.4231
  - Loss Nl Nl: 0.3291
  - Loss Nso Za: 0.5106
  - Loss Ny Mw: 2.7346
  - Loss Oci Fr: 5.0983
  - Loss Om Et: 0.2297
  - Loss Or In: 2.5432
  - Loss Pa In: 0.7753
  - Loss Pl Pl: 0.7309
  - Loss Ps Af: 1.0454
  - Loss Pt Br: 0.9782
  - Loss Ro Ro: 3.5829
  - Loss Ru Ru: 0.0598
  - Loss Rup Bg: 0.1695
  - Loss Sd Arab In: 2.6198
  - Loss Sk