xlsr_exp1_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
metrics:
  - wer
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: 0.4228
  • Cer: 0.1091
  • Wer: 0.3025

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: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Cer Wer
1.5566 0.94 2000 1.0226 0.2632 0.6184
1.179 1.89 4000 0.7682 0.2001 0.4990
1.0432 2.83 6000 0.6633 0.1749 0.4516
0.9413 3.77 8000 0.6159 0.1624 0.4259
0.8765 4.72 10000 0.5792 0.1538 0.4061
0.8248 5.66 12000 0.5456 0.1446 0.3877
0.7714 6.6 14000 0.5316 0.1397 0.3710
0.7388 7.55 16000 0.5172 0.1356 0.3657
0.6912 8.49 18000 0.4892 0.1291 0.3508
0.6549 9.43 20000 0.4694 0.1241 0.3397
0.614 10.37 22000 0.4615 0.1205 0.3309
0.5901 11.32 24000 0.4489 0.1177 0.3215
0.555 12.26 26000 0.4419 0.1148 0.3163
0.5377 13.2 28000 0.4320 0.1122 0.3103
0.5253 14.15 30000 0.4251 0.1102 0.3052

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.5
  • Tokenizers 0.14.1