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700-fine-tuned-whisper-base-full

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whisper
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metadata
language:
  - en
license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper base fine tuned full - ashe194
    results: []

Visualize in Weights & Biases

Whisper base fine tuned full - ashe194

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

  • Loss: 0.0034
  • Wer: 0.3422
  • Cer: 0.3439
  • Wer Ortho: 0.5124

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: 4e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer Wer Ortho
No log 0.9935 76 0.0065 0.4277 0.2934 0.7385
No log 2.0 153 0.0035 0.3707 0.3717 0.5275
No log 2.9804 228 0.0034 0.3422 0.3439 0.5124

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1