YonaKhine/finetuned-w2v2-bert-burmese-asr

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finetuned-w2v2-bert-burmese-asr

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the OpenSLR-80 Burmese Speech Dataset dataset. It achieves the following results on the evaluation set:

• —Loss: 0.3886
• —Wer: 0.4256

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 5e-05
• —trainbatchsize: 16
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 32
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 500
• —num_epochs: 10
• —mixedprecisiontraining: Native AMP

Training results

🔊 Real Example Evaluation

🎤 Audio Sample

You can listen to an example where a user says:

မင်္ဂလာ ပါ တွေ့ရတာဝမ်းသာပါတယ် ရှင်

📝 Model Transcription

မင်္ဂလာ ပါ တွေ့ရတာ ဝမ်းသပါတယ် ရှင်

✅ Reference

မင်္ဂလာ ပါ တွေ့ရတာဝမ်းသာပါတယ် ရှင်

📉 Word Error Rate (WER)

WER ≈ 0.10 – minor vowel difference only, excellent semantic preservation.

🎧 Audio Playback

Download and listen: burmese_test.wav

Framework versions

• —Transformers 4.51.3
• —Pytorch 2.6.0+cu124
• —Datasets 3.6.0
• —Tokenizers 0.21.1