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README.md
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- thennal/IMaSC
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- vrclc/openslr63
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- thennal/indic_tts_ml
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model-index:
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- name: XLSR-WithLM-Malayalam
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results:
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- type: wer
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value: 52.9
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name: WER
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---
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# XLSR-
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [IMASC](https://huggingface.co/datasets/thennal/IMaSC), [Indic TTS Malayalam](https://huggingface.co/datasets/thennal/indic_tts_ml), [OpenSLR Malayalam Train split](https://huggingface.co/datasets/vrclc/openslr63) datasets.
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It achieves the following results on the evaluation set:
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- Loss: 0.1395
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- Wer: 0.2952
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### Training hyperparameters
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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- thennal/IMaSC
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- vrclc/openslr63
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- thennal/indic_tts_ml
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- kavyamanohar/ml-sentences
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model-index:
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- name: XLSR-WithLM-Malayalam
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results:
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- type: wer
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value: 52.9
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name: WER
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---
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# XLSR-WithLM-Malayalam
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [IMASC](https://huggingface.co/datasets/thennal/IMaSC), [Indic TTS Malayalam](https://huggingface.co/datasets/thennal/indic_tts_ml), [OpenSLR Malayalam Train split](https://huggingface.co/datasets/vrclc/openslr63) datasets.
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It achieves the following results on the evaluation set:
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- Loss: 0.1395
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- Wer: 0.2952
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Trigram Language Model Trained using KENLM Library on [kavyamanohar/ml-sentences](https://huggingface.co/datasets/kavyamanohar/ml-sentences) dataset
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### Training hyperparameters
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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