README.md

metadata

language:
  - vi
license: apache-2.0
tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
datasets:
  - common_voice
metrics:
  - wer
model-index:
  - name: wav2vec2-common_voice-vi
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: COMMON_VOICE - VI
          type: common_voice
          config: vi
          split: train+validation
          args: 'Config: vi, Training split: train+validation, Eval split: test'
        metrics:
          - name: Wer
            type: wer
            value: 1

wav2vec2-common_voice-vi

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - VI dataset. It achieves the following results on the evaluation set:

• Loss: 28.9053
• Wer: 1.0

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: 0.0003
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 200
• total_train_batch_size: 200
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 15.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.25.1
• Pytorch 1.12.1+cu116
• Datasets 2.6.1
• Tokenizers 0.13.1