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Mnong-ASR-v3

Automatic Speech Recognition
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whisper
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Mnong-ASR-v3 / README.md
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metadata
language:
  - vi
license: apache-2.0
base_model: openai/whisper-base
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper Base Mnong
    results: []

Whisper Base Mnong

This model is a fine-tuned version of openai/whisper-base on the MnongAudio-v2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7309
  • Wer: 78.4474

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.2709 2.0325 1000 1.3573 121.7936
0.5929 4.0650 2000 0.9105 81.5333
0.2907 6.0976 3000 0.7671 80.9065
0.204 8.1301 4000 0.7309 78.4474

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1