71 lines
1.6 KiB
Markdown
71 lines
1.6 KiB
Markdown
---
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tags:
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- generated_from_keras_callback
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model-index:
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- name: wav2vec2-xls-r-300m-mixed
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# wav2vec2-xls-r-300m-mixed
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Finetuned https://huggingface.co/facebook/wav2vec2-xls-r-300m on https://github.com/huseinzol05/malaya-speech/tree/master/data/mixed-stt
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This model was finetuned on 3 languages,
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1. Malay
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2. Singlish
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3. Mandarin
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**This model trained on a single RTX 3090 Ti 24GB VRAM, provided by https://mesolitica.com/**.
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## Evaluation set
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Evaluation set from https://github.com/huseinzol05/malaya-speech/tree/master/pretrained-model/prepare-stt with sizes,
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```
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len(malay), len(singlish), len(mandarin)
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-> (765, 3579, 614)
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```
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It achieves the following results on the evaluation set based on [evaluate-gpu.ipynb](evaluate-gpu.ipynb):
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Mixed evaluation,
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```
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CER: 0.0481054244857041
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WER: 0.1322198446007387
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CER with LM: 0.041196586938584696
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WER with LM: 0.09880169127621556
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```
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Malay evaluation,
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```
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CER: 0.051636391937588406
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WER: 0.19561999547293663
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CER with LM: 0.03917689630621449
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WER with LM: 0.12710746406824835
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```
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Singlish evaluation,
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```
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CER: 0.0494915200071987
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WER: 0.12763802881676573
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CER with LM: 0.04271234986432335
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WER with LM: 0.09677160640413336
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```
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Mandarin evaluation,
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```
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CER: 0.035626554824269824
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WER: 0.07993515937860181
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CER with LM: 0.03487760945087219
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WER with LM: 0.07536807168546154
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```
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Language model from https://huggingface.co/huseinzol05/language-model-bahasa-manglish-combined |