wav2vec2-baseline / README.md
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metadata
license: cc-by-nc-4.0
base_model: nguyenvulebinh/wav2vec2-base-vi
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: wav2vec2-baseline
    results: []

wav2vec2-baseline

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

  • Loss: nan
  • 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: 8e-06
  • train_batch_size: 32
  • 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
  • num_epochs: 30.0

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.43 100 inf 1.2580
No log 0.85 200 inf 1.0
No log 1.28 300 inf 1.0
No log 1.71 400 inf 1.0
12.36 2.14 500 inf 1.0
12.36 2.56 600 inf 1.0
12.36 2.99 700 inf 1.0
12.36 3.42 800 inf 1.0
12.36 3.85 900 inf 1.0
8.4674 4.27 1000 inf 1.0
8.4674 4.7 1100 inf 1.0
8.4674 5.13 1200 inf 1.0
8.4674 5.56 1300 inf 1.0
8.4674 5.98 1400 inf 1.0
6.9866 6.41 1500 inf 1.0
6.9866 6.84 1600 inf 1.0
6.9866 7.26 1700 inf 1.0
6.9866 7.69 1800 inf 1.0
6.9866 8.12 1900 inf 1.0
6.8089 8.55 2000 inf 1.0
6.8089 8.97 2100 inf 1.0
6.8089 9.4 2200 inf 1.0
6.8089 9.83 2300 inf 1.0
6.8089 10.26 2400 inf 1.0
6.7847 10.68 2500 inf 1.0
6.7847 11.11 2600 inf 1.0
6.7847 11.54 2700 inf 1.0
6.7847 11.97 2800 inf 1.0
6.7847 12.39 2900 inf 1.0
6.7941 12.82 3000 inf 1.0
6.7941 13.25 3100 inf 1.0
6.7941 13.68 3200 inf 1.0
6.7941 14.1 3300 inf 1.0
6.7941 14.53 3400 inf 1.0
6.7956 14.96 3500 inf 1.0
6.7956 15.38 3600 inf 1.0
6.7956 15.81 3700 inf 1.0
6.7956 16.24 3800 inf 1.0
6.7956 16.67 3900 inf 1.0
6.8102 17.09 4000 inf 1.0
6.8102 17.52 4100 inf 1.0
6.8102 17.95 4200 inf 1.0
6.8102 18.38 4300 inf 1.0
6.8102 18.8 4400 inf 1.0
6.7761 19.23 4500 inf 1.0
6.7761 19.66 4600 inf 1.0
6.7761 20.09 4700 inf 1.0
6.7761 20.51 4800 inf 1.0
6.7761 20.94 4900 inf 1.0
6.8063 21.37 5000 inf 1.0
6.8063 21.79 5100 inf 1.0
6.8063 22.22 5200 inf 1.0
6.8063 22.65 5300 inf 1.0
6.8063 23.08 5400 inf 1.0
6.7934 23.5 5500 inf 1.0
6.7934 23.93 5600 inf 1.0
6.7934 24.36 5700 inf 1.0
6.7934 24.79 5800 inf 1.0
6.7934 25.21 5900 inf 1.0
6.7819 25.64 6000 inf 1.0
6.7819 26.07 6100 inf 1.0
6.7819 26.5 6200 inf 1.0
6.7819 26.92 6300 inf 1.0
6.7819 27.35 6400 inf 1.0
6.8278 27.78 6500 inf 1.0
6.8278 28.21 6600 inf 1.0
6.8278 28.63 6700 inf 1.0
6.8278 29.06 6800 nan 1.0
6.8278 29.49 6900 nan 1.0
6.7427 29.91 7000 nan 1.0

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.0
  • Datasets 2.14.4
  • Tokenizers 0.13.3