SakshiRathi77/wav2vec2-large-xlsr-300m-hi-kagglex

datasets:

• —mozilla-foundation/commonvoice15_0
• —mozilla-foundation/commonvoice13_0 language:
• —hi metrics:
• —cer
• —wer libraryname: transformers pipelinetag: automatic-speech-recognition model-index:
• —name: whisper-small-hi-cv results:
• —task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 15 type: mozilla-foundation/commonvoice15_0 args: hi metrics:
• —name: Test WER type: wer value: 13.9913
• —name: Test CER type: cer value: 5.8844

• —task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 13 type: mozilla-foundation/commonvoice13_0 args: hi metrics:
• —name: Test WER type: wer value: 23.3824
• —name: Test CER type: cer value: 10.5288

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Model Details

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on this dataset . It achieves the following results on the evaluation set:

• —Loss: 0.3691
• —Wer: 0.3285
• —Cer: 0.0875

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0001
• —trainbatchsize: 32
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 128
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 300
• —num_epochs: 100

Training results

Framework versions

• —Transformers 4.33.0
• —Pytorch 2.0.0
• —Datasets 2.1.0
• —Tokenizers 0.13.3

SPACE

Automatic Speech Recognization in hindi