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metadata
base_model: distil-whisper/distil-large-v3
datasets:
  - audiofolder
library_name: peft
license: mit
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: distil_whisper-v3-LoRA-en_students_test_2
    results: []

distil_whisper-v3-LoRA-en_students_test_2

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

  • Loss: 0.6839
  • Wer: 18.4361

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: 28
  • eval_batch_size: 28
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 100000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.5189 0.4444 500 1.1913 25.9108
1.1727 0.8889 1000 0.9531 24.5396
1.1341 1.3333 1500 0.8688 22.2761
1.0152 1.7778 2000 0.8174 20.8792
1.0589 2.2222 2500 0.7855 20.7595
0.9793 2.6667 3000 0.7611 22.2846
0.9594 3.1111 3500 0.7442 20.3860
1.0031 3.5556 4000 0.7303 18.5045
0.9525 4.0 4500 0.7199 18.1054
0.8729 4.4444 5000 0.7105 19.3170
1.0031 4.8889 5500 0.7028 19.7446
0.9273 5.3333 6000 0.6966 19.7189
0.9174 5.7778 6500 0.6896 18.4475
0.8842 6.2222 7000 0.6839 18.4361

Framework versions

  • PEFT 0.11.1
  • Transformers 4.42.4
  • Pytorch 2.1.0+cu118
  • Datasets 2.20.0
  • Tokenizers 0.19.1