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null | null | transformers |
# GPT2-Spanish
GPT2-Spanish is a language generation model trained from scratch with 11.5GB of Spanish texts and with a Byte Pair Encoding (BPE) tokenizer that was trained for this purpose. The parameters used are the same as the small version of the original OpenAI GPT2 model.
## Corpus
This model was trained with a... | {"language": "es", "license": "mit", "tags": ["GPT-2", "Spanish", "ebooks", "nlg"], "datasets": ["ebooks"], "widget": [{"text": "Quisiera saber que va a suceder"}]} | text-generation | DeepESP/gpt2-spanish | [
"transformers",
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"GPT-2",
"Spanish",
"ebooks",
"nlg",
"es",
"dataset:ebooks",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #tf #jax #gpt2 #text-generation #GPT-2 #Spanish #ebooks #nlg #es #dataset-ebooks #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# GPT2-Spanish
GPT2-Spanish is a language generation model trained from scratch with 11.5GB of Spanish texts and with a Byte Pair Encoding (BPE) tokenizer that was trained for this purpose. The parameters used are the same as the small version of the original OpenAI GPT2 model.
## Corpus
This model was trained with a... | [
"# GPT2-Spanish\nGPT2-Spanish is a language generation model trained from scratch with 11.5GB of Spanish texts and with a Byte Pair Encoding (BPE) tokenizer that was trained for this purpose. The parameters used are the same as the small version of the original OpenAI GPT2 model.",
"## Corpus\nThis model was trai... | [
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0.09831351786... |
null | null | transformers |
# bert-base-bg-cs-pl-ru-cased
SlavicBERT\[1\] \(Slavic \(bg, cs, pl, ru\), cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) was trained on Russian News and four Wikipedias: Bulgarian, Czech, Polish, and Russian. Subtoken vocabulary was built using this data. Multilingual BERT was used as an initialization for... | {"language": ["bg", "cs", "pl", "ru"]} | feature-extraction | DeepPavlov/bert-base-bg-cs-pl-ru-cased | [
"transformers",
"pytorch",
"jax",
"bert",
"feature-extraction",
"bg",
"cs",
"pl",
"ru",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"bg",
"cs",
"pl",
"ru"
] | TAGS
#transformers #pytorch #jax #bert #feature-extraction #bg #cs #pl #ru #endpoints_compatible #region-us
|
# bert-base-bg-cs-pl-ru-cased
SlavicBERT\[1\] \(Slavic \(bg, cs, pl, ru\), cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) was trained on Russian News and four Wikipedias: Bulgarian, Czech, Polish, and Russian. Subtoken vocabulary was built using this data. Multilingual BERT was used as an initialization for... | [
"# bert-base-bg-cs-pl-ru-cased\n\nSlavicBERT\\[1\\] \\(Slavic \\(bg, cs, pl, ru\\), cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) was trained on Russian News and four Wikipedias: Bulgarian, Czech, Polish, and Russian. Subtoken vocabulary was built using this data. Multilingual BERT was used as an initia... | [
"TAGS\n#transformers #pytorch #jax #bert #feature-extraction #bg #cs #pl #ru #endpoints_compatible #region-us \n",
"# bert-base-bg-cs-pl-ru-cased\n\nSlavicBERT\\[1\\] \\(Slavic \\(bg, cs, pl, ru\\), cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) was trained on Russian News and four Wikipedias: Bulgaria... | [
40,
200
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"passage: TAGS\n#transformers #pytorch #jax #bert #feature-extraction #bg #cs #pl #ru #endpoints_compatible #region-us \n# bert-base-bg-cs-pl-ru-cased\n\nSlavicBERT\\[1\\] \\(Slavic \\(bg, cs, pl, ru\\), cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) was trained on Russian News and four Wikipedias: Bulga... | [
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null | null | transformers |
# bert-base-cased-conversational
Conversational BERT \(English, cased, 12‑layer, 768‑hidden, 12‑heads, 110M parameters\) was trained on the English part of Twitter, Reddit, DailyDialogues\[1\], OpenSubtitles\[2\], Debates\[3\], Blogs\[4\], Facebook News Comments. We used this training data to build the vocabulary of ... | {"language": "en"} | feature-extraction | DeepPavlov/bert-base-cased-conversational | [
"transformers",
"pytorch",
"jax",
"bert",
"feature-extraction",
"en",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #bert #feature-extraction #en #endpoints_compatible #region-us
|
# bert-base-cased-conversational
Conversational BERT \(English, cased, 12‑layer, 768‑hidden, 12‑heads, 110M parameters\) was trained on the English part of Twitter, Reddit, DailyDialogues\[1\], OpenSubtitles\[2\], Debates\[3\], Blogs\[4\], Facebook News Comments. We used this training data to build the vocabulary of ... | [
"# bert-base-cased-conversational\n\nConversational BERT \\(English, cased, 12‑layer, 768‑hidden, 12‑heads, 110M parameters\\) was trained on the English part of Twitter, Reddit, DailyDialogues\\[1\\], OpenSubtitles\\[2\\], Debates\\[3\\], Blogs\\[4\\], Facebook News Comments. We used this training data to build th... | [
"TAGS\n#transformers #pytorch #jax #bert #feature-extraction #en #endpoints_compatible #region-us \n",
"# bert-base-cased-conversational\n\nConversational BERT \\(English, cased, 12‑layer, 768‑hidden, 12‑heads, 110M parameters\\) was trained on the English part of Twitter, Reddit, DailyDialogues\\[1\\], OpenSubti... | [
34,
385
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"passage: TAGS\n#transformers #pytorch #jax #bert #feature-extraction #en #endpoints_compatible #region-us \n# bert-base-cased-conversational\n\nConversational BERT \\(English, cased, 12‑layer, 768‑hidden, 12‑heads, 110M parameters\\) was trained on the English part of Twitter, Reddit, DailyDialogues\\[1\\], OpenSu... | [
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0.013... |
null | null | transformers |
# bert-base-multilingual-cased-sentence
Sentence Multilingual BERT \(101 languages, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) is a representation‑based sentence encoder for 101 languages of Multilingual BERT. It is initialized with Multilingual BERT and then fine‑tuned on english MultiNLI\[1\] and on d... | {"language": ["multilingual"]} | feature-extraction | DeepPavlov/bert-base-multilingual-cased-sentence | [
"transformers",
"pytorch",
"jax",
"bert",
"feature-extraction",
"multilingual",
"arxiv:1704.05426",
"arxiv:1809.05053",
"arxiv:1908.10084",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"1704.05426",
"1809.05053",
"1908.10084"
] | [
"multilingual"
] | TAGS
#transformers #pytorch #jax #bert #feature-extraction #multilingual #arxiv-1704.05426 #arxiv-1809.05053 #arxiv-1908.10084 #endpoints_compatible #region-us
|
# bert-base-multilingual-cased-sentence
Sentence Multilingual BERT \(101 languages, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) is a representation‑based sentence encoder for 101 languages of Multilingual BERT. It is initialized with Multilingual BERT and then fine‑tuned on english MultiNLI\[1\] and on d... | [
"# bert-base-multilingual-cased-sentence\n\nSentence Multilingual BERT \\(101 languages, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) is a representation‑based sentence encoder for 101 languages of Multilingual BERT. It is initialized with Multilingual BERT and then fine‑tuned on english MultiNLI\\[1\\... | [
"TAGS\n#transformers #pytorch #jax #bert #feature-extraction #multilingual #arxiv-1704.05426 #arxiv-1809.05053 #arxiv-1908.10084 #endpoints_compatible #region-us \n",
"# bert-base-multilingual-cased-sentence\n\nSentence Multilingual BERT \\(101 languages, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) ... | [
60,
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"passage: TAGS\n#transformers #pytorch #jax #bert #feature-extraction #multilingual #arxiv-1704.05426 #arxiv-1809.05053 #arxiv-1908.10084 #endpoints_compatible #region-us \n# bert-base-multilingual-cased-sentence\n\nSentence Multilingual BERT \\(101 languages, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\... | [
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-0.0591867... |
null | null | transformers | # distilrubert-base-cased-conversational
Conversational DistilRuBERT \(Russian, cased, 6‑layer, 768‑hidden, 12‑heads, 135.4M parameters\) was trained on OpenSubtitles\[1\], [Dirty](https://d3.ru/), [Pikabu](https://pikabu.ru/), and a Social Media segment of Taiga corpus\[2\] (as [Conversational RuBERT](https://huggingf... | {"language": ["ru"]} | null | DeepPavlov/distilrubert-base-cased-conversational | [
"transformers",
"pytorch",
"distilbert",
"ru",
"arxiv:2205.02340",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"2205.02340"
] | [
"ru"
] | TAGS
#transformers #pytorch #distilbert #ru #arxiv-2205.02340 #endpoints_compatible #region-us
| distilrubert-base-cased-conversational
======================================
Conversational DistilRuBERT (Russian, cased, 6‑layer, 768‑hidden, 12‑heads, 135.4M parameters) was trained on OpenSubtitles[1], Dirty, Pikabu, and a Social Media segment of Taiga corpus[2] (as Conversational RuBERT).
Our DistilRuBERT was ... | [] | [
"TAGS\n#transformers #pytorch #distilbert #ru #arxiv-2205.02340 #endpoints_compatible #region-us \n"
] | [
36
] | [
"passage: TAGS\n#transformers #pytorch #distilbert #ru #arxiv-2205.02340 #endpoints_compatible #region-us \n"
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0.041608043015003204,
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0.03401293605566025,
0.1757916808128357,
0.1854594498872757,
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0.0274437... |
null | null | transformers | # distilrubert-tiny-cased-conversational
Conversational DistilRuBERT-tiny \(Russian, cased, 3‑layers, 264‑hidden, 12‑heads, 10.4M parameters\) was trained on OpenSubtitles\[1\], [Dirty](https://d3.ru/), [Pikabu](https://pikabu.ru/), and a Social Media segment of Taiga corpus\[2\] (as [Conversational RuBERT](https://hug... | {"language": ["ru"]} | null | DeepPavlov/distilrubert-tiny-cased-conversational-v1 | [
"transformers",
"pytorch",
"distilbert",
"ru",
"arxiv:2205.02340",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"2205.02340"
] | [
"ru"
] | TAGS
#transformers #pytorch #distilbert #ru #arxiv-2205.02340 #endpoints_compatible #region-us
| distilrubert-tiny-cased-conversational
======================================
Conversational DistilRuBERT-tiny (Russian, cased, 3‑layers, 264‑hidden, 12‑heads, 10.4M parameters) was trained on OpenSubtitles[1], Dirty, Pikabu, and a Social Media segment of Taiga corpus[2] (as Conversational RuBERT). It can be consider... | [] | [
"TAGS\n#transformers #pytorch #distilbert #ru #arxiv-2205.02340 #endpoints_compatible #region-us \n"
] | [
36
] | [
"passage: TAGS\n#transformers #pytorch #distilbert #ru #arxiv-2205.02340 #endpoints_compatible #region-us \n"
] | [
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0.03401293605566025,
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0.1854594498872757,
-0.04804740101099014,
0.0274437... |
null | null | transformers | WARNING: This is `distilrubert-small-cased-conversational` model uploaded with wrong name. This one is the same as [distilrubert-small-cased-conversational](https://huggingface.co/DeepPavlov/distilrubert-small-cased-conversational). `distilrubert-tiny-cased-conversational` could be found in [distilrubert-tiny-cased-co... | {"language": ["ru"]} | null | DeepPavlov/distilrubert-tiny-cased-conversational | [
"transformers",
"pytorch",
"distilbert",
"ru",
"arxiv:2205.02340",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"2205.02340"
] | [
"ru"
] | TAGS
#transformers #pytorch #distilbert #ru #arxiv-2205.02340 #endpoints_compatible #region-us
| WARNING: This is 'distilrubert-small-cased-conversational' model uploaded with wrong name. This one is the same as distilrubert-small-cased-conversational. 'distilrubert-tiny-cased-conversational' could be found in distilrubert-tiny-cased-conversational-v1.
distilrubert-small-cased-conversational
====================... | [] | [
"TAGS\n#transformers #pytorch #distilbert #ru #arxiv-2205.02340 #endpoints_compatible #region-us \n"
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0.09749598801136017,
0.03401293605566025,
0.1757916808128357,
0.1854594498872757,
-0.04804740101099014,
0.0274437... |
null | null | transformers | # RoBERTa Large model fine-tuned on Winogrande
This model was fine-tuned on Winogrande dataset (XL size) in sequence classification task format, meaning that original pairs of sentences
with corresponding options filled in were separated, shuffled and classified independently of each other.
## Model description
## ... | {"language": ["en"], "datasets": ["winogrande"], "widget": [{"text": "The roof of Rachel's home is old and falling apart, while Betty's is new. The home value of </s> Rachel is lower."}, {"text": "The wooden doors at my friends work are worse than the wooden desks at my work, because the </s> desks material is cheaper.... | text-classification | DeepPavlov/roberta-large-winogrande | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:winogrande",
"arxiv:1907.11692",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"1907.11692"
] | [
"en"
] | TAGS
#transformers #pytorch #roberta #text-classification #en #dataset-winogrande #arxiv-1907.11692 #autotrain_compatible #endpoints_compatible #region-us
| # RoBERTa Large model fine-tuned on Winogrande
This model was fine-tuned on Winogrande dataset (XL size) in sequence classification task format, meaning that original pairs of sentences
with corresponding options filled in were separated, shuffled and classified independently of each other.
## Model description
## ... | [
"# RoBERTa Large model fine-tuned on Winogrande\n\nThis model was fine-tuned on Winogrande dataset (XL size) in sequence classification task format, meaning that original pairs of sentences\nwith corresponding options filled in were separated, shuffled and classified independently of each other.",
"## Model descr... | [
"TAGS\n#transformers #pytorch #roberta #text-classification #en #dataset-winogrande #arxiv-1907.11692 #autotrain_compatible #endpoints_compatible #region-us \n",
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0.07074423134326935,
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0.10433332... |
null | null | transformers |
# rubert-base-cased-conversational
Conversational RuBERT \(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) was trained on OpenSubtitles\[1\], [Dirty](https://d3.ru/), [Pikabu](https://pikabu.ru/), and a Social Media segment of Taiga corpus\[2\]. We assembled a new vocabulary for Conversational RuBER... | {"language": ["ru"]} | feature-extraction | DeepPavlov/rubert-base-cased-conversational | [
"transformers",
"pytorch",
"jax",
"bert",
"feature-extraction",
"ru",
"endpoints_compatible",
"has_space",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #jax #bert #feature-extraction #ru #endpoints_compatible #has_space #region-us
|
# rubert-base-cased-conversational
Conversational RuBERT \(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) was trained on OpenSubtitles\[1\], Dirty, Pikabu, and a Social Media segment of Taiga corpus\[2\]. We assembled a new vocabulary for Conversational RuBERT model on this data and initialized the... | [
"# rubert-base-cased-conversational\n\nConversational RuBERT \\(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) was trained on OpenSubtitles\\[1\\], Dirty, Pikabu, and a Social Media segment of Taiga corpus\\[2\\]. We assembled a new vocabulary for Conversational RuBERT model on this data and ini... | [
"TAGS\n#transformers #pytorch #jax #bert #feature-extraction #ru #endpoints_compatible #has_space #region-us \n",
"# rubert-base-cased-conversational\n\nConversational RuBERT \\(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) was trained on OpenSubtitles\\[1\\], Dirty, Pikabu, and a Social Medi... | [
38,
273
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"passage: TAGS\n#transformers #pytorch #jax #bert #feature-extraction #ru #endpoints_compatible #has_space #region-us \n# rubert-base-cased-conversational\n\nConversational RuBERT \\(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) was trained on OpenSubtitles\\[1\\], Dirty, Pikabu, and a Social M... | [
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0.060444846749305725,
0.03776245191693306,
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0.054424211382865906,
0.048125... |
null | null | transformers |
# rubert-base-cased-sentence
Sentence RuBERT \(Russian, cased, 12-layer, 768-hidden, 12-heads, 180M parameters\) is a representation‑based sentence encoder for Russian. It is initialized with RuBERT and fine‑tuned on SNLI\[1\] google-translated to russian and on russian part of XNLI dev set\[2\]. Sentence representat... | {"language": ["ru"]} | feature-extraction | DeepPavlov/rubert-base-cased-sentence | [
"transformers",
"pytorch",
"jax",
"bert",
"feature-extraction",
"ru",
"arxiv:1508.05326",
"arxiv:1809.05053",
"arxiv:1908.10084",
"endpoints_compatible",
"has_space",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"1508.05326",
"1809.05053",
"1908.10084"
] | [
"ru"
] | TAGS
#transformers #pytorch #jax #bert #feature-extraction #ru #arxiv-1508.05326 #arxiv-1809.05053 #arxiv-1908.10084 #endpoints_compatible #has_space #region-us
|
# rubert-base-cased-sentence
Sentence RuBERT \(Russian, cased, 12-layer, 768-hidden, 12-heads, 180M parameters\) is a representation‑based sentence encoder for Russian. It is initialized with RuBERT and fine‑tuned on SNLI\[1\] google-translated to russian and on russian part of XNLI dev set\[2\]. Sentence representat... | [
"# rubert-base-cased-sentence\n\nSentence RuBERT \\(Russian, cased, 12-layer, 768-hidden, 12-heads, 180M parameters\\) is a representation‑based sentence encoder for Russian. It is initialized with RuBERT and fine‑tuned on SNLI\\[1\\] google-translated to russian and on russian part of XNLI dev set\\[2\\]. Sentence... | [
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"# rubert-base-cased-sentence\n\nSentence RuBERT \\(Russian, cased, 12-layer, 768-hidden, 12-heads, 180M parameters\\) is a representation‑based s... | [
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null | null | transformers |
# rubert-base-cased
RuBERT \(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) was trained on the Russian part of Wikipedia and news data. We used this training data to build a vocabulary of Russian subtokens and took a multilingual version of BERT‑base as an initialization for RuBERT\[1\].
08.11.202... | {"language": ["ru"]} | feature-extraction | DeepPavlov/rubert-base-cased | [
"transformers",
"pytorch",
"jax",
"bert",
"feature-extraction",
"ru",
"arxiv:1905.07213",
"endpoints_compatible",
"has_space",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"1905.07213"
] | [
"ru"
] | TAGS
#transformers #pytorch #jax #bert #feature-extraction #ru #arxiv-1905.07213 #endpoints_compatible #has_space #region-us
|
# rubert-base-cased
RuBERT \(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\) was trained on the Russian part of Wikipedia and news data. We used this training data to build a vocabulary of Russian subtokens and took a multilingual version of BERT‑base as an initialization for RuBERT\[1\].
08.11.202... | [
"# rubert-base-cased\n\nRuBERT \\(Russian, cased, 12‑layer, 768‑hidden, 12‑heads, 180M parameters\\) was trained on the Russian part of Wikipedia and news data. We used this training data to build a vocabulary of Russian subtokens and took a multilingual version of BERT‑base as an initialization for RuBERT\\[1\\].\... | [
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null | null | transformers |
# XLM-RoBERTa-Large-En-Ru-MNLI
xlm-roberta-large-en-ru finetuned on mnli. | {"language": ["en", "ru"], "tags": ["xlm-roberta", "xlm-roberta-large", "xlm-roberta-large-en-ru", "xlm-roberta-large-en-ru-mnli"], "datasets": ["glue", "mnli"], "model_index": [{"name": "mnli", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "GLUE MNLI", "type":... | text-classification | DeepPavlov/xlm-roberta-large-en-ru-mnli | [
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"xlm-roberta",
"text-classification",
"xlm-roberta-large",
"xlm-roberta-large-en-ru",
"xlm-roberta-large-en-ru-mnli",
"en",
"ru",
"dataset:glue",
"dataset:mnli",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"en",
"ru"
] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #xlm-roberta-large #xlm-roberta-large-en-ru #xlm-roberta-large-en-ru-mnli #en #ru #dataset-glue #dataset-mnli #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# XLM-RoBERTa-Large-En-Ru-MNLI
xlm-roberta-large-en-ru finetuned on mnli. | [
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"# XLM-RoBERTa-Large-En-Ru-MNLI\n\nxlm-roberta-large-en-ru finetuned ... | [
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null | null | transformers |
# XLM-RoBERTa-Large-En-Ru
## Model description
This model is a version XLM-RoBERTa with embeddings and vocabulary reduced to most frequent tokens in English and Russian.
| {"language": ["en", "ru"]} | feature-extraction | DeepPavlov/xlm-roberta-large-en-ru | [
"transformers",
"pytorch",
"xlm-roberta",
"feature-extraction",
"en",
"ru",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"en",
"ru"
] | TAGS
#transformers #pytorch #xlm-roberta #feature-extraction #en #ru #endpoints_compatible #region-us
|
# XLM-RoBERTa-Large-En-Ru
## Model description
This model is a version XLM-RoBERTa with embeddings and vocabulary reduced to most frequent tokens in English and Russian.
| [
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null | null | transformers |
# Wav2Vec2-Large-XLSR-53-Lithuanian
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Lithuanian using the [Common Voice](https://huggingface.co/datasets/common_voice)
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The mod... | {"language": "lt", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "model-index": [{"name": "XLSR Wav2Vec2 Lithuanina by Deividas Mataciunas", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recogn... | automatic-speech-recognition | DeividasM/wav2vec2-large-xlsr-53-lithuanian | [
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"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"lt",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"lt"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #lt #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-Lithuanian
Fine-tuned facebook/wav2vec2-large-xlsr-53 in Lithuanian using the Common Voice
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluate... | [
"# Wav2Vec2-Large-XLSR-53-Lithuanian\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 in Lithuanian using the Common Voice\n\nWhen using this model, make sure that your speech input is sampled at 16kHz.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe mod... | [
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0.07139... |
null | null | transformers | Need to work with OpenDelta
```
from transformers import AutoModelForSeq2SeqLM
t5 = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
from opendelta import AutoDeltaModel
delta = AutoDeltaModel.from_finetuned("DeltaHub/lora_t5-base_mrpc", backbone_model=t5)
delta.log()
```
| {} | null | DeltaHub/lora_t5-base_mrpc | [
"transformers",
"pytorch",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #endpoints_compatible #region-us
| Need to work with OpenDelta
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null | null | transformers |
# Modèle de détection de 4 sentiments avec FlauBERT (mixed, negative, objective, positive)
### Comment l'utiliser ?
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from transformers import pipeline
loaded_tokenizer = AutoTokenizer.from_pretrained('flaubert/flaubert_large_cased'... | {"language": "fr", "tags": ["sentiments", "text-classification", "flaubert", "french", "flaubert-large"]} | text-classification | DemangeJeremy/4-sentiments-with-flaubert | [
"transformers",
"pytorch",
"flaubert",
"text-classification",
"sentiments",
"french",
"flaubert-large",
"fr",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #flaubert #text-classification #sentiments #french #flaubert-large #fr #autotrain_compatible #endpoints_compatible #region-us
| Modèle de détection de 4 sentiments avec FlauBERT (mixed, negative, objective, positive)
========================================================================================
### Comment l'utiliser ?
Résultats de l'évaluation du modèle
-----------------------------------
Pour toute utilisation de ce modèle, m... | [
"### Comment l'utiliser ?\n\n\nRésultats de l'évaluation du modèle\n-----------------------------------\n\n\n\nPour toute utilisation de ce modèle, merci d'utiliser cette citation :\n\n\n\n> \n> Jérémy Demange, Four sentiments with FlauBERT, (2021), Hugging Face repository, <URL\n> \n> \n>"
] | [
"TAGS\n#transformers #pytorch #flaubert #text-classification #sentiments #french #flaubert-large #fr #autotrain_compatible #endpoints_compatible #region-us \n",
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"passage: TAGS\n#transformers #pytorch #flaubert #text-classification #sentiments #french #flaubert-large #fr #autotrain_compatible #endpoints_compatible #region-us \n### Comment l'utiliser ?\n\n\nRésultats de l'évaluation du modèle\n-----------------------------------\n\n\n\nPour toute utilisation de ce modèle, me... | [
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null | null | transformers |
# Asuna Yuuki DialoGPT Model | {"tags": ["conversational"]} | text-generation | Denny29/DialoGPT-medium-asunayuuki | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Asuna Yuuki DialoGPT Model | [
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0.03340093791484833,
0.110955... |
null | null | null | title: ArcaneGAN
emoji: 🚀
colorFrom: blue
colorTo: blue
sdk: gradio
app_file: app.py
pinned: false | {} | null | Despin89/test | [
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#region-us
| title: ArcaneGAN
emoji:
colorFrom: blue
colorTo: blue
sdk: gradio
app_file: URL
pinned: false | [] | [
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null | null | transformers |
# Token classification for FOODs.
Detects foods in sentences.
Currently, only supports spanish. Multiple words foods are detected as one entity.
## To-do
- English support.
- Negation support.
- Quantity tags.
- Psychosocial tags. | {"widget": [{"text": "El paciente se alimenta de pan, sopa de calabaza y coca-cola"}]} | token-classification | Dev-DGT/food-dbert-multiling | [
"transformers",
"pytorch",
"distilbert",
"token-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #token-classification #autotrain_compatible #endpoints_compatible #region-us
|
# Token classification for FOODs.
Detects foods in sentences.
Currently, only supports spanish. Multiple words foods are detected as one entity.
## To-do
- English support.
- Negation support.
- Quantity tags.
- Psychosocial tags. | [
"# Token classification for FOODs.\n\nDetects foods in sentences. \n\nCurrently, only supports spanish. Multiple words foods are detected as one entity.",
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] | [
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null | null | transformers |
# Miku DialogGPT Model | {"tags": ["conversational"]} | text-generation | Devid/DialoGPT-small-Miku | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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|
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null | null | null | The default Prism model available at https://github.com/thompsonb/prism. See the [README.md](https://github.com/thompsonb/prism/blob/master/README.md) file for more information.
**LICENCE NOTICE**
```
MIT License
Copyright (c) Brian Thompson
Portions of this software are copied from fairseq (http... | {"license": "mit"} | null | Devrim/prism-default | [
"license:mit",
"region:us"
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#license-mit #region-us
| The default Prism model available at URL See the URL file for more information.
LICENCE NOTICE
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# Wav2Vec2-Large-XLSR-Welsh
This model has moved to https://huggingface.co/techiaith/wav2vec2-xlsr-ft-cy
| {"language": "cy", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-xlsr-welsh (by Dewi Bryn Jones, fine tuning week - March 2021)", "results": [{"task": {"type": "automatic... | automatic-speech-recognition | DewiBrynJones/wav2vec2-large-xlsr-welsh | [
"audio",
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"speech",
"xlsr-fine-tuning-week",
"cy",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"cy"
] | TAGS
#audio #automatic-speech-recognition #speech #xlsr-fine-tuning-week #cy #dataset-common_voice #license-apache-2.0 #model-index #region-us
|
# Wav2Vec2-Large-XLSR-Welsh
This model has moved to URL
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null | null | transformers |
<!-- 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. -->
# opus-mt-en-ro-finetuned-en-to-ro
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ro](https://huggingface.co/Helsi... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wmt16"], "metrics": ["bleu"], "model-index": [{"name": "opus-mt-en-ro-finetuned-en-to-ro", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "wmt16", "type": "wmt16", "a... | text2text-generation | DiegoAlysson/opus-mt-en-ro-finetuned-en-to-ro | [
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"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #generated_from_trainer #dataset-wmt16 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| opus-mt-en-ro-finetuned-en-to-ro
================================
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ro on the wmt16 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2915
* Bleu: 27.9273
* Gen Len: 34.0935
Model description
-----------------
More information... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1\n* mixed\\_prec... | [
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null | null | transformers |
# Harry Potter DialoGPT Model | {"tags": ["conversational"]} | text-generation | Dilmk2/DialoGPT-small-harrypotter | [
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null | null | transformers |
# V DialoGPT Model | {"tags": ["conversational"]} | text-generation | Dimedrolza/DialoGPT-small-cyberpunk | [
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"gpt2",
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"conversational",
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null | null | transformers |
# HomerBot: A conversational chatbot imitating Homer Simpson
This model is a fine-tuned [DialoGPT](https://huggingface.co/microsoft/DialoGPT-medium) (medium version) on Simpsons [scripts](https://www.kaggle.com/datasets/pierremegret/dialogue-lines-of-the-simpsons).
More specifically, we fine-tune DialoGPT-medium for... | {"language": ["en"], "tags": ["conversational"]} | text-generation | jesseD/homer-bot | [
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"autotrain_compatible",
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"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"en"
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#transformers #pytorch #gpt2 #text-generation #conversational #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# HomerBot: A conversational chatbot imitating Homer Simpson
This model is a fine-tuned DialoGPT (medium version) on Simpsons scripts.
More specifically, we fine-tune DialoGPT-medium for 3 epochs on 10K (character utterance, Homer's response) pairs
For more details, check out our git repo containing all the code. ... | [
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null | null | transformers |
# Harry Potter DialoGPT Medium Model | {"tags": ["conversational"]} | text-generation | Doiman/DialoGPT-medium-harrypotter | [
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"endpoints_compatible",
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"region:us"
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null | null | transformers |
# Rick DialoGPT Model | {"tags": ["conversational"]} | text-generation | DongHai/DialoGPT-small-rick | [
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null | null | transformers |
<!-- 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. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["matthews_correlation"], "model-index": [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "ar... | text-classification | DongHyoungLee/distilbert-base-uncased-finetuned-cola | [
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"generated_from_trainer",
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"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-cola
======================================
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7335
* Matthews Correlation: 0.5356
Model description
-----------------
More informa... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
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null | null | transformers | The Reader model is for Korean Question Answering
The backbone model is deepset/xlm-roberta-large-squad2.
It is a finetuned model with KorQuAD-v1 dataset.
As a result of verification using KorQuAD evaluation dataset, it showed approximately 87% and 92% respectively for the EM score and F1 score.
Thank you | {} | question-answering | Dongjae/mrc2reader | [
"transformers",
"pytorch",
"xlm-roberta",
"question-answering",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #question-answering #endpoints_compatible #region-us
| The Reader model is for Korean Question Answering
The backbone model is deepset/xlm-roberta-large-squad2.
It is a finetuned model with KorQuAD-v1 dataset.
As a result of verification using KorQuAD evaluation dataset, it showed approximately 87% and 92% respectively for the EM score and F1 score.
Thank you | [] | [
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null | null | transformers |
<!-- 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. -->
# Wayne_NLP_mT5
This model was trained only english datasets.
if you want trained korean + english model
go to wayne_mulang_mT5.
... | {"tags": ["generated_from_trainer"], "datasets": ["cnn_dailymail"], "model-index": [{"name": "Wayne_NLP_mT5", "results": []}]} | text2text-generation | Waynehillsdev/Wayne_NLP_mT5 | [
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"generated_from_trainer",
"dataset:cnn_dailymail",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Wayne_NLP_mT5
This model was trained only english datasets.
if you want trained korean + english model
go to wayne_mulang_mT5.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
#... | [
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null | null | transformers |
<!-- 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. -->
# Waynehills-STT-doogie-server
This model is a fine-tuned version of [Doogie/Waynehills-STT-doogie-server](https://huggingface.co/... | {"license": "apache-2.0", "tags": ["generated_from_trainer"]} | automatic-speech-recognition | Waynehillsdev/Waynehills-STT-doogie-server | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
|
# Waynehills-STT-doogie-server
This model is a fine-tuned version of Doogie/Waynehills-STT-doogie-server on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
##... | [
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Waynehills_summary_tensorflow
This model is a fine-tuned version of [KETI-AIR/ke-t5-base-ko](https://huggingface.co/KETI-AIR/ke-t5-bas... | {"tags": ["generated_from_keras_callback"], "model-index": [{"name": "Waynehills_summary_tensorflow", "results": []}]} | text2text-generation | Waynehillsdev/Waynehills_summary_tensorflow | [
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"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Waynehills_summary_tensorflow
This model is a fine-tuned version of KETI-AIR/ke-t5-base-ko on an unknown dataset.
It achieves the following results on the evaluation set:
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More... | [
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<!-- 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. -->
# wav2vec2-base-timit-demo-colab
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-timit-demo-colab", "results": []}]} | automatic-speech-recognition | Waynehillsdev/wav2vec2-base-timit-demo-colab | [
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#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-timit-demo-colab
==============================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4180
* Wer: 0.3392
Model description
-----------------
More information needed
Intended uses & limi... | [
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null | null | transformers | Model for Extraction-based MRC
original model : klue/roberta-large
Designed for ODQA Competition | {} | question-answering | Doohae/roberta | [
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"roberta",
"question-answering",
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"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #endpoints_compatible #region-us
| Model for Extraction-based MRC
original model : klue/roberta-large
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#Rick DialoGPT model | {"tags": ["conversational"]} | text-generation | Doquey/DialoGPT-small-Luisbot1 | [
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] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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#Rick DialoGPT model | [] | [
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null | null | transformers |
#Michael | {"tags": "conversational"} | text-generation | Doquey/DialoGPT-small-Michaelbot | [
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"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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null | null | transformers |
# Celestia Ludenburg DiabloGPT Model | {"tags": ["conversational"]} | text-generation | Doxophobia/DialoGPT-medium-celeste | [
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"pytorch",
"gpt2",
"text-generation",
"conversational",
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"endpoints_compatible",
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"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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null | null | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# tmp_qubhe07
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
## M... | {"tags": ["generated_from_keras_callback"], "model-index": [{"name": "tmp_qubhe07", "results": []}]} | text-classification | DoyyingFace/doyying_bert_first_again | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us
|
# tmp_qubhe07
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
... | [
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null | null | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# dummy-model
This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
It ac... | {"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "dummy-model", "results": []}]} | fill-mask | DoyyingFace/dummy-model | [
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|
# dummy-model
This model is a fine-tuned version of camembert-base on an unknown dataset.
It achieves the following results on the evaluation set:
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Tr... | [
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null | null | transformers |
# Legacies DialoGPT Model | {"tags": ["conversational"]} | text-generation | Dragoniod1596/DialoGPT-small-Legacies | [
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"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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null | null | transformers |
#Uncle Iroh DialoGPT Model | {"tags": ["conversational"]} | text-generation | Dreyzin/DialoGPT-medium-avatar | [
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"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
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] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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|
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["ab"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "ab", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-ab-CV7 | [
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"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
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"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"ab"
] | TAGS
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|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - AB dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5620
* Wer: 0.5651
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
p... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-ab-CV7 --dataset mozilla-foundation/common\\_voice\\_7\\_0 --config ab --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition... | [
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["ab"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "", "results": []}]} | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-ab-v4 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"ab",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"ab"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ab #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - AB dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6178
* Wer: 0.5794
Model description
-----------------
More information needed
Intended uses & limitations
----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.00025\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* ... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-as-g1
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["as"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "as", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-as-g1 | [
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"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"as"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #as #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-as-g1
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - AS dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3327
* Wer: 0.5744
### Evaluation Commands
1. To evalu... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-as-g1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config as --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-as-v9
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["as"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "as", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-as-v9 | [
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"tensorboard",
"wav2vec2",
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"as",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"as"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #as #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-as-v9
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1679
* Wer: 0.5761
### Evaluation Command
1. To evaluate on mozilla-foundation/commo... | [
"### Evaluation Command\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-as-v9 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config as --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-c... | [
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null | null | null |
<!-- 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. -->
### Note: Files are missing. Probably, didn't get (git)pushed properly. :(
This model is a fine-tuned version of [facebook/wav2... | {"language": ["as"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "as", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-as-with-LM-v2", ... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-as-with-LM-v2 | [
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
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"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
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] | TAGS
#automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #as #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-common_voice #license-apache-2.0 #model-index #region-us
| ### Note: Files are missing. Probably, didn't get (git)pushed properly. :(
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1679
* Wer: 0.5761
Model description
-----------------
More information n... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-bas-v1
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["bas"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "bas", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xl... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-bas-v1 | [
"transformers",
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"tensorboard",
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"automatic-speech-recognition",
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"generated_from_trainer",
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"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
... | 2022-03-02T23:29:04+00:00 | [] | [
"bas"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #bas #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-bas-v1
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - BAS dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5997
* Wer: 0.3870
### Evaluation Commands
1. To ev... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-bas-v1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config bas --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognitio... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-bg-d2
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["bg"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "bg", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-bg-d2", "re... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-bg-d2 | [
"transformers",
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"tensorboard",
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"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"end... | 2022-03-02T23:29:04+00:00 | [] | [
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| wav2vec2-large-xls-r-300m-bg-d2
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - BG dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3421
* Wer: 0.2860
### Evaluation Commands
1. To evalu... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-d2 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config bg --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["bg"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "bg", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-bg-v1 | [
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"... | 2022-03-02T23:29:04+00:00 | [] | [
"bg"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #bg #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - BG dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5197
* Wer: 0.4689
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
p... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-v1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config bg --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #bg #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-br-d10
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["br"], "license": "apache-2.0", "tags": ["generated_from_trainer", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-br-d10", "results": [{"task": {"type": "automatic-speech-recognition... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-br-d10 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"robust-speech-event",
"hf-asr-leaderboard",
"br",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"br"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #br #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-br-d10
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - BR dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1382
* Wer: 0.4895
### Evaluation Commands
1. To eva... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-br-d10 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config br --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #br #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Evaluation Commands\n\n\n1. To evaluate o... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-br-d2
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["br"], "license": "apache-2.0", "tags": ["generated_from_trainer", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-br-d2", "results": [{"task": {"type": "automatic-speech-recognition"... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-br-d2 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"robust-speech-event",
"hf-asr-leaderboard",
"br",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"br"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #br #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-br-d2
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - BR dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1257
* Wer: 0.4631
### Evaluation Commands
1. To evalu... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-br-d2 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config br --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #br #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Evaluation Commands\n\n\n1. To evaluate o... | [
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0.087860658... |
null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-gn-k1
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["gn"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "gn", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-gn-k1", "re... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-gn-k1 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"gn",
"robust-speech-event",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"end... | 2022-03-02T23:29:04+00:00 | [] | [
"gn"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #gn #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-gn-k1
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - GN dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9220
* Wer: 0.6631
### Evaluation Commands
1. To evalu... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-gn-k1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config gn --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #gn #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
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0.104585133... |
null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-hi-CV7
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["hi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "hi", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-hi-CV7", "r... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-hi-CV7 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"hi",
"robust-speech-event",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"end... | 2022-03-02T23:29:04+00:00 | [] | [
"hi"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #hi #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hi-CV7
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - HI dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6588
* Wer: 0.2987
### Evaluation Commands
1. To eva... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-CV7 --dataset mozilla-foundation/common\\_voice\\_7\\_0 --config hi --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #hi #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-hi-cv8-b2
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"language": ["hi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-hi-cv8-b2", "results": [{"task": {"type": "automatic-speech-re... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8-b2 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"robust-speech-event",
"hf-asr-leaderboard",
"hi",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"hi"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #robust-speech-event #hf-asr-leaderboard #hi #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hi-cv8-b2
===================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - HI dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7322
* Wer: 0.3469
### Evaluation Commands
1. ... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8-b2 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config hi --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognit... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #robust-speech-event #hf-asr-leaderboard #hi #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/com... | [
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0.1259451... |
null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-hi-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["hi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "hi", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"hi",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"hi"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hi #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hi-cv8
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - HI dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6510
* Wer: 0.3179
### Evaluation Commands
1. To eva... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config hi --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hi #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us ... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-hi-d3
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["hi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "hi", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-hi-d3 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"hi",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"hi"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #hi #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hi-d3
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - HI dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7988
* Wer: 0.3713
###Evaluation Commands
1. To evalua... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.000388\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsil... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-hi-wx1
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["hi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "hf-asr-leaderboard", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-hi-wx1", "results": [{"task": {"type": "automatic-speech-recog... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-hi-wx1 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"robust-speech-event",
"hi",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"hi"
] | TAGS
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| wav2vec2-large-xls-r-300m-hi-wx1
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 -HI dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6552
* Wer: 0.3200
Evaluation Commands
1. To evaluate... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.00024\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #robust-speech-event #hi #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-hsb-v1
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["hsb"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "hsb", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xl... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v1 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
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"hsb",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
... | 2022-03-02T23:29:04+00:00 | [] | [
"hsb"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hsb #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hsb-v1
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - HSB dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5684
* Wer: 0.4402
### Evaluation Commands
1. To ev... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config hsb --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognitio... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hsb #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-hsb-v2
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["hsb"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "hsb", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xl... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v2 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"hsb",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
... | 2022-03-02T23:29:04+00:00 | [] | [
"hsb"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hsb #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hsb-v2
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - HSB dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5328
* Wer: 0.4596
### Evaluation Commands
1. To ev... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v2 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config hsb --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognitio... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hsb #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-hsb-v3
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["hsb"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "hsb", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xl... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v3 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
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"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
... | 2022-03-02T23:29:04+00:00 | [] | [
"hsb"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hsb #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hsb-v3
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - HSB dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6549
* Wer: 0.4827
### Evaluation Commands
1. To ev... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v3 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config hsb --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognitio... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #hsb #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us... | [
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["kk"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "kk", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-kk-with-LM | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"kk",
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"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"kk"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #kk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - KK dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7149
* Wer: 0.451
Evaluation Commands
===================
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.000222\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsil... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #kk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
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0.10574796795845032... |
null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-maltese
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fa... | {"language": ["mt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "mt", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"]} | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-maltese | [
"transformers",
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"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
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"mozilla-foundation/common_voice_8_0",
"mt",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"endpoints_compati... | 2022-03-02T23:29:04+00:00 | [] | [
"mt"
] | TAGS
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| wav2vec2-large-xls-r-300m-maltese
=================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - MT dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2994
* Wer: 0.2781
Model description
---------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #mt #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
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0.09725914150476456,
0.10661628842353821,
0.08105621486902237,
0.1396939158... |
null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-mr-v2
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["mr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "mr", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-mr-v2", "re... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"mr",
"robust-speech-event",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"end... | 2022-03-02T23:29:04+00:00 | [] | [
"mr"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mr #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-mr-v2
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - MR dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8729
* Wer: 0.4942
### Evaluation Commands
1. To evalu... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config mr --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mr #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-myv-v1
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["myv"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "myv", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xl... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-myv-v1 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"myv",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
... | 2022-03-02T23:29:04+00:00 | [] | [
"myv"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #myv #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #regi... | wav2vec2-large-xls-r-300m-myv-v1
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - MYV dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8537
* Wer: 0.6160
### Evaluation Commands
1. To ev... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-myv-v1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config myv --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognitio... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #myv #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-or-d5
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["or"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "or", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-or-d5 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"or",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"or"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #or #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-or-d5
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - OR dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9571
* Wer: 0.5450
### Evaluation Commands
1. To evalu... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-or-d5 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config or --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #or #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us ... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-or-dx12
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fa... | {"language": ["or"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "or", "robust-speech-event"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-or-dx12", "resul... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-or-dx12 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"or",
"robust-speech-event",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoi... | 2022-03-02T23:29:04+00:00 | [] | [
"or"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #or #robust-speech-event #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-or-dx12
=================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4638
* Wer: 0.5602
### Evaluation Commands
1. To evaluate on mozilla-foundation/... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-or-dx12 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config or --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognitio... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #or #robust-speech-event #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Evaluation ... | [
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["pa-IN"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "pa-IN", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-pa-IN... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"pa-IN",
"robust-speech-event",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compati... | 2022-03-02T23:29:04+00:00 | [] | [
"pa-IN"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #pa-IN #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - PA-IN dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0855
* Wer: 0.4755
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config pa-IN --split test --log\\_outputs\n\n\n2. To evaluate on speech-recog... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #pa-IN #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Evaluation Com... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-sat-a3
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["sat"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "sat", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xl... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-sat-a3 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"sat",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
... | 2022-03-02T23:29:04+00:00 | [] | [
"sat"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #sat #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-sat-a3
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - SAT dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8961
* Wer: 0.3976
### Evaluation Commands
1. To ev... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-sat-a3 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config sat --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognitio... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #sat #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us... | [
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null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-sat-final
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"language": ["sat"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "sat", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xl... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-sat-final | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"sat",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
... | 2022-03-02T23:29:04+00:00 | [] | [
"sat"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #sat #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-sat-final
===================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - SAT dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8012
* Wer: 0.3815
### Evaluation Commands
1.... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-sat-final --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config sat --split test --log\\_outputs\n\n\n2. To evaluate on speech-recogni... | [
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["sl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "sl"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"sl",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"sl"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sl #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - SL dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2756
* Wer: 0.2279
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
p... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config sl --split test --log\\_outputs\n\n\n2. To evaluate on speech-reco... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sl #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### E... | [
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0.087864100933... |
null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["sl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "sl"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v2 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"sl",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"sl"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sl #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - SL dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2855
* Wer: 0.2401
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
p... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-sl-with-LM-v2 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config sl --split test --log\\_outputs\n\n\n2. To evaluate on speech-reco... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sl #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### E... | [
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0.0876354351639... |
null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-sr-v4
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["sr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "sr"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"sr",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"sr"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sr #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-sr-v4
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - SR dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5570
* Wer: 0.3038
### Evaluation Commands
1. To evalu... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-sr-v4 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config sr --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sr #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us ... | [
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0.0696941167... |
null | null | transformers |
<!-- 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. -->
# wav2vec2-large-xls-r-300m-vot-final-a2
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.... | {"language": ["vot"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "vot", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-vot-final-a2", "results": [{"task":... | automatic-speech-recognition | DrishtiSharma/wav2vec2-large-xls-r-300m-vot-final-a2 | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"vot",
"robust-speech-event",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"regi... | 2022-03-02T23:29:04+00:00 | [] | [
"vot"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #vot #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-vot-final-a2
======================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - VOT dataset.
It achieves the following results on the evaluation set:
* Loss: 2.8745
* Wer: 0.8333
### Evaluation Command... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-large-xls-r-300m-vot-final-a2 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config vot --split test --log\\_outputs\n\n\n2. To evaluate on speech-reco... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #vot #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Evaluation Commands\n\n\n1.... | [
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0.0692849... |
null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["kk"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "kk", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-xls-r-300m... | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-300m-kk-n2 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"kk",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"kk"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #kk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - KK dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7149
* Wer: 0.451
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
py... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-xls-r-300m-kk-n2 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config kk --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-commun... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #kk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### E... | [
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0.07175511121749... |
null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["mt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "mt", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-xls-r-300m... | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-300m-mt-o1 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"mt",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"mt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - MT dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1987
* Wer: 0.1920
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
p... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-xls-r-300m-mt-o1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config mt --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-commun... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### E... | [
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"passage: TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n##... | [
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0.07990851253271103,
0.06719172745... |
null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["pa-IN"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "pa-IN", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-xls-... | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-300m-pa-IN-r5 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"pa-IN",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
... | 2022-03-02T23:29:04+00:00 | [] | [
"pa-IN"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #pa-IN #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - PA-IN dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8881
* Wer: 0.4175
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-xls-r-300m-pa-IN-r5 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config pa-IN --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #pa-IN #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["rm-sursilv"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "hf-asr-leaderboard", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-xls-r-300m-rm-sursilv-d11", "results": [{"task": {"type": "automatic-sp... | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-300m-rm-sursilv-d11 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"rm-sursilv"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - RM-SURSILV dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2511
* Wer: 0.2415
#### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test ... | [
"#### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-xls-r-300m-rm-sursilv-d11 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config rm-sursilv --split test --log\\_outputs\n\n\n2. To evaluate on speech-... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"#### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\... | [
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null | null | transformers | <!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the... | {"language": ["rm-vallader"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "rm-vallader", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "w... | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-300m-rm-vallader-d1 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"rm-vallader",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-in... | 2022-03-02T23:29:04+00:00 | [] | [
"rm-vallader"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #rm-vallader #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - RM-VALLADER dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2754
* Wer: 0.2831
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test ... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-xls-r-300m-rm-vallader-d1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config rm-vallader --split test --log\\_outputs\n\n\n2. To evaluate on speech-... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #rm-vallader #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",... | [
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["myv"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "myv", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-xls-r-my... | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-myv-a1 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"myv",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
... | 2022-03-02T23:29:04+00:00 | [] | [
"myv"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #myv #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - MYV dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0356
* Wer: 0.6524
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-xls-r-myv-a1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config myv --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-community... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #myv #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### ... | [
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["pa-IN"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "", "results": []}]} | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-pa-IN-a1 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"pa-IN"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - PA-IN dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1508
* Wer: 0.4908
Model description
-----------------
More information needed
Intended uses & limitations
-------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* lear... | [
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null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["sl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "sl"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-xls-r-sl-a... | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-sl-a1 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"sl",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"sl"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sl #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - SL dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2756
* Wer: 0.2279
### Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
p... | [
"### Evaluation Commands\n\n\n1. To evaluate on mozilla-foundation/common\\_voice\\_8\\_0 with test split\n\n\npython URL --model\\_id DrishtiSharma/wav2vec2-xls-r-sl-a1 --dataset mozilla-foundation/common\\_voice\\_8\\_0 --config sl --split test --log\\_outputs\n\n\n2. To evaluate on speech-recognition-community-v... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #sl #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### E... | [
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0.108265139162... |
null | null | transformers |
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["sl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "sl", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-xls-r-sl-a... | automatic-speech-recognition | DrishtiSharma/wav2vec2-xls-r-sl-a2 | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"sl",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | 2022-03-02T23:29:04+00:00 | [] | [
"sl"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #sl #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - SL dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2855
* Wer: 0.2401
##Evaluation Commands
1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split
pyt... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #sl #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... | [
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0.09004782140254974,
0.09027086943387985,
0.09058769047260284,
0.13555879890... |
null | null | transformers |
<!-- 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. -->
# distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "distilbert-base-uncased-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "con... | token-classification | Duc/distilbert-base-uncased-finetuned-ner | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-ner
=====================================
This model is a fine-tuned version of distilbert-base-uncased on the conll2003 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0604
* Precision: 0.9262
* Recall: 0.9375
* F1: 0.9318
* Accuracy: 0.9841
Model des... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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null | null | transformers |
# Harry Potter DialoGPT Model | {"tags": ["conversational"]} | text-generation | DueLinx0402/DialoGPT-small-harrypotter | [
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"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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null | null | transformers |
<!-- 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. -->
## This model achieves WER on common-voice ro test split of WER: 12.457178%
# wav2vec2-xls-r-300m-romanian
This model is a fine-tun... | {"license": "apache-2.0", "tags": ["generated_from_trainer"]} | automatic-speech-recognition | Dumiiii/wav2vec2-xls-r-300m-romanian | [
"transformers",
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"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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|
## This model achieves WER on common-voice ro test split of WER: 12.457178%
# wav2vec2-xls-r-300m-romanian
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an common voice ro and RSS dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0836
- eval_wer: 0.0705
- eval_r... | [
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null | null | transformers |
# Alexia Bot Testing | {} | text-generation | Duugu/alexia-bot-test | [
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"region:us"
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null | null | transformers |
# My Awesome Model | {"tags": ["conversational"]} | text-generation | Duugu/jakebot3000 | [
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"conversational",
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] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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null | null | transformers |
#Landcheese | {"tags": ["conversational"]} | text-generation | Dyzi/DialoGPT-small-landcheese | [
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] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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#Landcheese | [] | [
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null | null | transformers |
<!-- 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. -->
# out
This model is a fine-tuned version of [/1TB_SSD/SB_AI/out_epoch1/out/checkpoint-1115000/](https://huggingface.co//1TB_SSD/SB... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "out", "results": []}]} | text2text-generation | EColi/sponsorblock-base-v1 | [
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"t5",
"text2text-generation",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| out
===
This model is a fine-tuned version of /1TB\_SSD/SB\_AI/out\_epoch1/out/checkpoint-1115000/ on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0645
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 1\n* seed: 2518227880\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2.0",
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null | null | transformers |
# Brooke DialoGPT Model | {"tags": ["conversational"]} | text-generation | EEE/DialoGPT-medium-brooke | [
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"text-generation",
"conversational",
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"endpoints_compatible",
"text-generation-inference",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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null | null | transformers |
# Aang DialoGPT Model | {"tags": ["conversational"]} | text-generation | EEE/DialoGPT-small-aang | [
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"endpoints_compatible",
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] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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null | null | transformers |
# Yoda DialoGPT Model | {"tags": ["conversational"]} | text-generation | EEE/DialoGPT-small-yoda | [
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"text-generation",
"conversational",
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"endpoints_compatible",
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"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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null | null | transformers |
**IMPORTANT:** On the 5th of April 2022, we detected a mistake in the configuration file; thus, the model was not generating the summaries correctly, and it was underperforming in all scenarios. For this reason, if you had used the model until that day, we would be glad if you would re-evaluate the model if you are pu... | {"language": "ca", "tags": ["summarization"], "widget": [{"text": "La Universitat Polit\u00e8cnica de Val\u00e8ncia (UPV), a trav\u00e9s del projecte Atenea \u201cplataforma de dones, art i tecnologia\u201d i en col\u00b7laboraci\u00f3 amb les companyies tecnol\u00f2giques Metric Salad i Zetalab, ha digitalitzat i mode... | summarization | ELiRF/NASCA | [
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|
IMPORTANT: On the 5th of April 2022, we detected a mistake in the configuration file; thus, the model was not generating the summaries correctly, and it was underperforming in all scenarios. For this reason, if you had used the model until that day, we would be glad if you would re-evaluate the model if you are publis... | [
"# NASca and NASes: Two Monolingual Pre-Trained Models for Abstractive Summarization in Catalan and Spanish\n\nMost of the models proposed in the literature for abstractive summarization are generally suitable for the English language but not for other languages. Multilingual models were introduced to address that ... | [
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null | null | transformers | **IMPORTANT:** On the 5th of April 2022, we detected a mistake in the configuration file; thus, the model was not generating the summaries correctly, and it was underperforming in all scenarios. For this reason, if you had used the model until that day, we would be glad if you would re-evaluate the model if you are pub... | {"language": "es", "tags": ["summarization"], "widget": [{"text": "La Agencia Valenciana de la Innovaci\u00f3n (AVI) financia el desarrollo de un software que integra diferentes modelos y tecnolog\u00edas para la monitorizaci\u00f3n y an\u00e1lisis multiling\u00fce de las redes sociales. A trav\u00e9s de t\u00e9cnicas ... | summarization | ELiRF/NASES | [
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"# NASca and NASes: Two Monolingual Pre-Trained Models for Abstractive Summarization in Catalan and Spanish\n\nMost of the models proposed in the literature for abstractive summarization are generally suitable for the English language but not for other languages. Multilingual models were introduced to address that ... | [
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0.17435814... |
null | null | transformers | # CroSloEngual BERT
CroSloEngual BERT is a trilingual model, using bert-base architecture, trained on Croatian, Slovenian, and English corpora. Focusing on three languages, the model performs better than [multilingual BERT](https://huggingface.co/bert-base-multilingual-cased), while still offering an option for cross-l... | {"language": ["hr", "sl", "en", "multilingual"], "license": "cc-by-4.0"} | fill-mask | EMBEDDIA/crosloengual-bert | [
"transformers",
"pytorch",
"jax",
"bert",
"fill-mask",
"hr",
"sl",
"en",
"multilingual",
"arxiv:2006.07890",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"2006.07890"
] | [
"hr",
"sl",
"en",
"multilingual"
] | TAGS
#transformers #pytorch #jax #bert #fill-mask #hr #sl #en #multilingual #arxiv-2006.07890 #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| # CroSloEngual BERT
CroSloEngual BERT is a trilingual model, using bert-base architecture, trained on Croatian, Slovenian, and English corpora. Focusing on three languages, the model performs better than multilingual BERT, while still offering an option for cross-lingual knowledge transfer, which a monolingual model wo... | [
"# CroSloEngual BERT\nCroSloEngual BERT is a trilingual model, using bert-base architecture, trained on Croatian, Slovenian, and English corpora. Focusing on three languages, the model performs better than multilingual BERT, while still offering an option for cross-lingual knowledge transfer, which a monolingual mo... | [
"TAGS\n#transformers #pytorch #jax #bert #fill-mask #hr #sl #en #multilingual #arxiv-2006.07890 #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# CroSloEngual BERT\nCroSloEngual BERT is a trilingual model, using bert-base architecture, trained on Croatian, Slovenian, and... | [
71,
101
] | [
"passage: TAGS\n#transformers #pytorch #jax #bert #fill-mask #hr #sl #en #multilingual #arxiv-2006.07890 #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n# CroSloEngual BERT\nCroSloEngual BERT is a trilingual model, using bert-base architecture, trained on Croatian, Slovenian, ... | [
-0.02857918106019497,
-0.03002042882144451,
-0.0013228324241936207,
0.09596967697143555,
0.030735529959201813,
0.006327140610665083,
0.1540680080652237,
0.020984303206205368,
0.12421358376741409,
-0.028371594846248627,
0.05265585333108902,
0.08676227182149887,
-0.0005933838547207415,
-0.00... |
null | null | transformers | # Usage
Load in transformers library with:
```
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/est-roberta")
model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/est-roberta")
```
# Est-RoBERTa
Est-RoBERTa model is a monolingual Estonian BERT-li... | {"language": ["et"], "license": "cc-by-sa-4.0"} | fill-mask | EMBEDDIA/est-roberta | [
"transformers",
"pytorch",
"camembert",
"fill-mask",
"et",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"et"
] | TAGS
#transformers #pytorch #camembert #fill-mask #et #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
| # Usage
Load in transformers library with:
# Est-RoBERTa
Est-RoBERTa model is a monolingual Estonian BERT-like model. It is closely related to French Camembert model URL The Estonian corpora used for training the model have 2.51 billion tokens in total. The subword vocabulary contains 40,000 tokens.
Est-RoBERTa was ... | [
"# Usage\nLoad in transformers library with:",
"# Est-RoBERTa\nEst-RoBERTa model is a monolingual Estonian BERT-like model. It is closely related to French Camembert model URL The Estonian corpora used for training the model have 2.51 billion tokens in total. The subword vocabulary contains 40,000 tokens.\n\nEst-... | [
"TAGS\n#transformers #pytorch #camembert #fill-mask #et #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# Usage\nLoad in transformers library with:",
"# Est-RoBERTa\nEst-RoBERTa model is a monolingual Estonian BERT-like model. It is closely related to French Camembert model UR... | [
51,
12,
82
] | [
"passage: TAGS\n#transformers #pytorch #camembert #fill-mask #et #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n# Usage\nLoad in transformers library with:# Est-RoBERTa\nEst-RoBERTa model is a monolingual Estonian BERT-like model. It is closely related to French Camembert model URL T... | [
-0.030650660395622253,
-0.15378575026988983,
-0.002755627268925309,
0.04529193043708801,
0.15375393629074097,
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0.1860322803258896,
0.018056273460388184,
0.08277209103107452,
-0.02707265131175518,
0.12712451815605164,
0.06396709382534027,
-0.03658338263630867,
0.20383... |
null | null | transformers | # FinEst BERT
FinEst BERT is a trilingual model, using bert-base architecture, trained on Finnish, Estonian, and English corpora. Focusing on three languages, the model performs better than [multilingual BERT](https://huggingface.co/bert-base-multilingual-cased), while still offering an option for cross-lingual knowled... | {"language": ["fi", "et", "en", "multilingual"], "license": "cc-by-4.0"} | fill-mask | EMBEDDIA/finest-bert | [
"transformers",
"pytorch",
"jax",
"bert",
"fill-mask",
"fi",
"et",
"en",
"multilingual",
"arxiv:2006.07890",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [
"2006.07890"
] | [
"fi",
"et",
"en",
"multilingual"
] | TAGS
#transformers #pytorch #jax #bert #fill-mask #fi #et #en #multilingual #arxiv-2006.07890 #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us
| # FinEst BERT
FinEst BERT is a trilingual model, using bert-base architecture, trained on Finnish, Estonian, and English corpora. Focusing on three languages, the model performs better than multilingual BERT, while still offering an option for cross-lingual knowledge transfer, which a monolingual model wouldn't.
Eval... | [
"# FinEst BERT\nFinEst BERT is a trilingual model, using bert-base architecture, trained on Finnish, Estonian, and English corpora. Focusing on three languages, the model performs better than multilingual BERT, while still offering an option for cross-lingual knowledge transfer, which a monolingual model wouldn't. ... | [
"TAGS\n#transformers #pytorch #jax #bert #fill-mask #fi #et #en #multilingual #arxiv-2006.07890 #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# FinEst BERT\nFinEst BERT is a trilingual model, using bert-base architecture, trained on Finnish, Estonian, and English corpora. Focusin... | [
67,
95
] | [
"passage: TAGS\n#transformers #pytorch #jax #bert #fill-mask #fi #et #en #multilingual #arxiv-2006.07890 #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us \n# FinEst BERT\nFinEst BERT is a trilingual model, using bert-base architecture, trained on Finnish, Estonian, and English corpora. Focu... | [
-0.04993933439254761,
-0.03267158567905426,
-0.0032079138327389956,
0.11249512434005737,
0.07179262489080429,
-0.005931683350354433,
0.174315944314003,
0.020063910633325577,
0.09168671071529388,
-0.03275713324546814,
0.040231507271528244,
0.02432258427143097,
0.03118063695728779,
0.1376775... |
null | null | transformers |
# LitLat BERT
LitLat BERT is a trilingual model, using xlm-roberta-base architecture, trained on Lithuanian, Latvian, and English corpora. Focusing on three languages, the model performs better than [multilingual BERT](https://huggingface.co/bert-base-multilingual-cased), while still offering an option for cross-lingu... | {"language": ["lt", "lv", "en", "multilingual"], "license": "cc-by-sa-4.0"} | fill-mask | EMBEDDIA/litlat-bert | [
"transformers",
"pytorch",
"xlm-roberta",
"fill-mask",
"lt",
"lv",
"en",
"multilingual",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 2022-03-02T23:29:04+00:00 | [] | [
"lt",
"lv",
"en",
"multilingual"
] | TAGS
#transformers #pytorch #xlm-roberta #fill-mask #lt #lv #en #multilingual #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
| LitLat BERT
===========
LitLat BERT is a trilingual model, using xlm-roberta-base architecture, trained on Lithuanian, Latvian, and English corpora. Focusing on three languages, the model performs better than multilingual BERT, while still offering an option for cross-lingual knowledge transfer, which a monolingual m... | [
"### Named entity recognition evaluation\n\n\nWe compare LitLat BERT with multilingual BERT (mBERT), XLM-RoBERTa (XLM-R) and monolingual Latvian BERT (LVBERT) (Znotins and Barzdins, 2020). The report the results as a macro F1 score of 3 named entity classes shared in all three datasets: person, location, organizati... | [
"TAGS\n#transformers #pytorch #xlm-roberta #fill-mask #lt #lv #en #multilingual #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Named entity recognition evaluation\n\n\nWe compare LitLat BERT with multilingual BERT (mBERT), XLM-RoBERTa (XLM-R) and monolingual Latvian BERT (L... | [
61,
93
] | [
"passage: TAGS\n#transformers #pytorch #xlm-roberta #fill-mask #lt #lv #en #multilingual #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n### Named entity recognition evaluation\n\n\nWe compare LitLat BERT with multilingual BERT (mBERT), XLM-RoBERTa (XLM-R) and monolingual Latvian BERT... | [
-0.09674447029829025,
-0.0018252881709486246,
-0.004506036173552275,
0.12975084781646729,
0.15220482647418976,
-0.03216265141963959,
0.08307357877492905,
0.03160207346081734,
0.09901057928800583,
0.02015255019068718,
0.029483366757631302,
0.05760719254612923,
-0.006441882811486721,
0.01833... |
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