finetune_v7 / README.md
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metadata
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: finetune_v7
    results: []

finetune_v7

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6387
  • Wer: 81.7276

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: 4
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 4
  • 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: 5
  • training_steps: 80
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 6.6667 10 0.6616 27.2425
No log 13.3333 20 0.6074 28.5714
No log 20.0 30 0.6377 28.5714
No log 26.6667 40 0.6221 32.5581
0.2362 33.3333 50 0.6255 103.9867
0.2362 40.0 60 0.6309 36.2126
0.2362 46.6667 70 0.6362 37.2093
0.2362 53.3333 80 0.6387 81.7276

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.2.0
  • Datasets 2.20.0
  • Tokenizers 0.19.1