asr-nepali / README.md
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - generated_from_trainer
metrics:
  - wer
  - accuracy
model-index:
  - name: asr-nepali
    results: []

asr-nepali

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Wer: 1.0
  • Cer: 0.9965
  • Accuracy: 0.0035

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: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 180
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer Accuracy
451.545 1.46 100 43.3285 1.0 0.9684 0.0316
194.4567 2.92 200 nan 1.0 0.9965 0.0035
0.0 4.38 300 nan 1.0 0.9965 0.0035
0.0 5.84 400 nan 1.0 0.9965 0.0035
0.0 7.3 500 nan 1.0 0.9965 0.0035
0.0 8.76 600 nan 1.0 0.9965 0.0035
0.0 10.22 700 nan 1.0 0.9965 0.0035
0.0 11.68 800 nan 1.0 0.9965 0.0035
0.0 13.14 900 nan 1.0 0.9965 0.0035
0.0 14.6 1000 nan 1.0 0.9965 0.0035
0.0 16.06 1100 nan 1.0 0.9965 0.0035
0.0 17.52 1200 nan 1.0 0.9965 0.0035
0.0 18.98 1300 nan 1.0 0.9965 0.0035
0.0 20.44 1400 nan 1.0 0.9965 0.0035
0.0 21.9 1500 nan 1.0 0.9965 0.0035
0.0 23.36 1600 nan 1.0 0.9965 0.0035
0.0 24.82 1700 nan 1.0 0.9965 0.0035
0.0 26.28 1800 nan 1.0 0.9965 0.0035
0.0 27.74 1900 nan 1.0 0.9965 0.0035
0.0 29.2 2000 nan 1.0 0.9965 0.0035

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0