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whisper-large-v2-finetuned

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whisper
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whisper-large-v2-finetuned / README.md
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metadata
base_model: openai/whisper-large-v2
datasets:
  - common_voice_16_1
library_name: peft
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: whisper-large-v2-finetuned
    results: []

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whisper-large-v2-finetuned

This model is a fine-tuned version of openai/whisper-large-v2 on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.9793
  • eval_wer: 108.5390
  • eval_runtime: 321.9393
  • eval_samples_per_second: 0.503
  • eval_steps_per_second: 0.012
  • epoch: 50.0
  • step: 400

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: 0.0001
  • train_batch_size: 50
  • eval_batch_size: 50
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 10
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Framework versions

  • PEFT 0.11.1
  • Transformers 4.42.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1