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metadata
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Sep26-Mixat-whisper-lg-3-transliteration
    results: []

Sep26-Mixat-whisper-lg-3-transliteration

This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7321
  • Wer: 40.6571

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.7747 0.4292 100 0.4311 36.6994
0.4882 0.8584 200 0.4418 35.7241
0.3749 1.2876 300 0.4387 40.5617
0.3644 1.7167 400 0.4506 40.1608
0.3451 2.1459 500 0.4571 42.6225
0.2678 2.5751 600 0.4558 38.1490
0.2737 3.0043 700 0.4406 38.5621
0.1576 3.4335 800 0.4937 42.0456
0.1653 3.8627 900 0.4995 41.7987
0.1113 4.2918 1000 0.5667 41.4100
0.0957 4.7210 1100 0.5606 39.9237
0.0817 5.1502 1200 0.6160 41.6984
0.0534 5.5794 1300 0.6003 42.2313
0.0549 6.0086 1400 0.5908 40.9724
0.0315 6.4378 1500 0.6655 40.5031
0.0364 6.8670 1600 0.7179 43.4389
0.0278 7.2961 1700 0.6839 42.8009
0.0251 7.7253 1800 0.6803 42.9891
0.0228 8.1545 1900 0.7166 42.3047
0.0197 8.5837 2000 0.7321 40.6571

Framework versions

  • Transformers 4.43.4
  • Pytorch 2.4.1
  • Datasets 3.0.0
  • Tokenizers 0.19.1