finetune_v15 / 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_v15
    results: []

finetune_v15

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: 0.7837
  • Wer: 193.6017

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: 16
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • 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 6.1538 10 0.7300 34.1589
No log 12.3077 20 0.7090 39.9381
No log 18.4615 30 0.7617 33.2559
No log 24.6154 40 0.7676 33.4107
0.223 30.7692 50 0.7749 199.6646
0.223 36.9231 60 0.7764 164.3189
0.223 43.0769 70 0.7827 202.6574
0.223 49.2308 80 0.7837 193.6017

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.2.0
  • Datasets 2.20.0
  • Tokenizers 0.19.1