xlsr_5p_ko-en / README.md
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - automatic-speech-recognition
  - ./sample_speech.py
  - generated_from_trainer
model-index:
  - name: ko-xlsr
    results: []

ko-xlsr

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

  • Loss: 0.4651
  • Cer: 0.0828

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: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss Cer
6.3673 3.17 1500 0.6104 0.1606
0.656 6.33 3000 0.4318 0.1129
0.4729 9.5 4500 0.4010 0.1028
0.3789 12.66 6000 0.3867 0.0977
0.3166 15.83 7500 0.3857 0.0936
0.267 18.99 9000 0.3891 0.0912
0.2286 22.16 10500 0.4074 0.0910
0.1967 25.32 12000 0.4079 0.0878
0.1712 28.49 13500 0.4289 0.0865
0.1493 31.65 15000 0.4456 0.0850
0.1333 34.82 16500 0.4573 0.0843
0.1191 37.98 18000 0.4633 0.0833

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.14.0