First update
Browse files- .gitattributes +1 -0
- README.md +214 -1
- config.json +3 -0
- optimizer.pt +3 -0
- pytorch_model.bin +3 -0
- rng_state.pth +3 -0
- scheduler.pt +3 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +3 -0
- trainer_state.json +3 -0
- training_args.bin +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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-
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---
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---
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tags:
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- Transformers
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- text-classification
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- multi-class-classification
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languages:
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- af-ZA
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- am-ET
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- ar-SA
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- az-AZ
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- bn-BD
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- cy-GB
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- da-DK
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- de-DE
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- el-GR
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- en-US
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- es-ES
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- fa-IR
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- fi-FI
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- fr-FR
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- he-IL
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- hi-IN
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- hu-HU
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- hy-AM
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- id-ID
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- is-IS
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- it-IT
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- ja-JP
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- jv-ID
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- ka-GE
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- km-KH
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- kn-IN
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- ko-KR
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- lv-LV
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- ml-IN
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- mn-MN
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- ms-MY
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- my-MM
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- nb-NO
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- nl-NL
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- pl-PL
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- pt-PT
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- ro-RO
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- ru-RU
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- sl-SL
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- sq-AL
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- sv-SE
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- sw-KE
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- ta-IN
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- te-IN
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- th-TH
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- tl-PH
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- tr-TR
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- ur-PK
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- vi-VN
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- zh-CN
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- zh-TW
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multilinguality:
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- af-ZA
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- am-ET
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- ar-SA
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- az-AZ
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- bn-BD
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64 |
+
- cy-GB
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+
- da-DK
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- de-DE
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- el-GR
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- en-US
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- es-ES
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- fa-IR
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- fi-FI
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- fr-FR
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- he-IL
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- hi-IN
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- hu-HU
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- hy-AM
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- id-ID
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- is-IS
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- it-IT
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- ja-JP
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- jv-ID
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- ka-GE
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- km-KH
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- kn-IN
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+
- ko-KR
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- lv-LV
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87 |
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- ml-IN
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- mn-MN
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- ms-MY
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- my-MM
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- nb-NO
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- nl-NL
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- pl-PL
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- pt-PT
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- ro-RO
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- ru-RU
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- sl-SL
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- sq-AL
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- sv-SE
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- sw-KE
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- ta-IN
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- te-IN
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- th-TH
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- tl-PH
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- tr-TR
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- ur-PK
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- vi-VN
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- zh-CN
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- zh-TW
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datasets:
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- qanastek/MASSIVE
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widget:
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- text: "wake me up at five am this week"
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- text: "je veux écouter la chanson de jacques brel encore une fois"
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- text: "quiero escuchar la canción de arijit singh una vez más"
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- text: "olly onde é que á um parque por perto onde eu possa correr"
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- text: "פרק הבא בפודקאסט בבקשה"
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- text: "亚马逊股价"
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- text: "найди билет на поезд в санкт-петербург"
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license: cc-by-4.0
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---
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**People Involved**
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* [LABRAK Yanis](https://www.linkedin.com/in/yanis-labrak-8a7412145/) (1)
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**Affiliations**
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1. [LIA, NLP team](https://lia.univ-avignon.fr/), Avignon University, Avignon, France.
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## Demo: How to use in HuggingFace Transformers Pipeline
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Requires [transformers](https://pypi.org/project/transformers/): ```pip install transformers```
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline
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model_name = 'qanastek/51-languages-classifier'
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSequenceClassification.from_pretrained(model_name)
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classifier = TextClassificationPipeline(model=model, tokenizer=tokenizer)
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res = classifier("פרק הבא בפודקאסט בבקשה")
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print(res)
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```
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Outputs:
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```python
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[{'label': 'fr-FR', 'score': 0.9998375177383423}]
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```
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## Training data
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[MASSIVE](https://huggingface.co/datasets/qanastek/MASSIVE) is a parallel dataset of > 1M utterances across 51 languages with annotations for the Natural Language Understanding tasks of intent prediction and slot annotation. Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing the SLURP dataset, composed of general Intelligent Voice Assistant single-shot interactions.
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## Evaluation results
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```plain
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precision recall f1-score support
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af-ZA 0.9821 0.9805 0.9813 2974
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am-ET 1.0000 1.0000 1.0000 2974
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ar-SA 0.9809 0.9822 0.9815 2974
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az-AZ 0.9946 0.9845 0.9895 2974
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bn-BD 0.9997 0.9990 0.9993 2974
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cy-GB 0.9970 0.9929 0.9949 2974
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da-DK 0.9575 0.9617 0.9596 2974
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de-DE 0.9906 0.9909 0.9908 2974
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el-GR 0.9997 0.9973 0.9985 2974
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en-US 0.9712 0.9866 0.9788 2974
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es-ES 0.9825 0.9842 0.9834 2974
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fa-IR 0.9940 0.9973 0.9956 2974
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fi-FI 0.9943 0.9946 0.9945 2974
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fr-FR 0.9963 0.9923 0.9943 2974
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he-IL 1.0000 0.9997 0.9998 2974
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hi-IN 1.0000 0.9980 0.9990 2974
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hu-HU 0.9983 0.9950 0.9966 2974
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hy-AM 1.0000 0.9993 0.9997 2974
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id-ID 0.9319 0.9291 0.9305 2974
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is-IS 0.9966 0.9943 0.9955 2974
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it-IT 0.9698 0.9926 0.9811 2974
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ja-JP 0.9987 0.9963 0.9975 2974
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jv-ID 0.9628 0.9744 0.9686 2974
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ka-GE 0.9993 0.9997 0.9995 2974
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km-KH 0.9867 0.9963 0.9915 2974
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kn-IN 1.0000 0.9993 0.9997 2974
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ko-KR 0.9917 0.9997 0.9956 2974
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lv-LV 0.9990 0.9950 0.9970 2974
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ml-IN 0.9997 0.9997 0.9997 2974
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mn-MN 0.9987 0.9966 0.9976 2974
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ms-MY 0.9359 0.9418 0.9388 2974
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my-MM 1.0000 0.9993 0.9997 2974
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nb-NO 0.9600 0.9533 0.9566 2974
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nl-NL 0.9850 0.9748 0.9799 2974
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pl-PL 0.9946 0.9923 0.9934 2974
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pt-PT 0.9885 0.9798 0.9841 2974
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ro-RO 0.9919 0.9916 0.9918 2974
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ru-RU 0.9976 0.9983 0.9980 2974
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sl-SL 0.9956 0.9939 0.9948 2974
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sq-AL 0.9936 0.9896 0.9916 2974
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sv-SE 0.9902 0.9842 0.9872 2974
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sw-KE 0.9867 0.9953 0.9910 2974
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ta-IN 1.0000 1.0000 1.0000 2974
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te-IN 1.0000 0.9997 0.9998 2974
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th-TH 1.0000 0.9983 0.9992 2974
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tl-PH 0.9929 0.9899 0.9914 2974
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tr-TR 0.9869 0.9872 0.9871 2974
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ur-PK 0.9983 0.9929 0.9956 2974
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vi-VN 0.9993 0.9973 0.9983 2974
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zh-CN 0.9812 0.9832 0.9822 2974
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zh-TW 0.9832 0.9815 0.9823 2974
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accuracy 0.9889 151674
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macro avg 0.9889 0.9889 0.9889 151674
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weighted avg 0.9889 0.9889 0.9889 151674
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```
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config.json
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version https://git-lfs.github.com/spec/v1
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optimizer.pt
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pytorch_model.bin
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rng_state.pth
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scheduler.pt
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sentencepiece.bpe.model
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special_tokens_map.json
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tokenizer.json
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tokenizer_config.json
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version https://git-lfs.github.com/spec/v1
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trainer_state.json
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training_args.bin
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