README.md

metadata

license: cc-by-nc-4.0
tags:
  - generated_from_trainer
base_model: nguyenvulebinh/wav2vec2-base-vi
datasets:
  - common_voice_16_1
metrics:
  - wer
model-index:
  - name: wav2vec2-common-voice-16_1_vi
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: common_voice_16_1
          type: common_voice_16_1
          config: vi
          split: None
          args: vi
        metrics:
          - type: wer
            value: 0.9998983326555511
            name: Wer

wav2vec2-common-voice-16_1_vi

This model is a fine-tuned version of nguyenvulebinh/wav2vec2-base-vi on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:

• Loss: 3.5323
• Wer: 0.9999

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: 0.0001
• train_batch_size: 8
• 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: 1000
• num_epochs: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
21.7841	4.2373	500	7.6684	0.9999
4.0045	8.4746	1000	3.5474	0.9999
3.4763	12.7119	1500	3.5357	0.9999
3.4721	16.9492	2000	3.5319	0.9999
3.4661	21.1864	2500	3.5321	0.9999
3.464	25.4237	3000	3.5315	0.9999
3.4732	29.6610	3500	3.5323	0.9999

Framework versions

• Transformers 4.40.0
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1