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Librarian Bot: Add base_model information to model (#1)
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metadata
license: apache-2.0
tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
base_model: openai/whisper-small
model-index:
  - name: openai/whisper-small
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: hu
          split: test
        metrics:
          - type: wer
            value: 30.637414764304772
            name: Wer

openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5649
  • Wer: 30.6374

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: 64
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0182 7.01 1000 0.4546 31.4735
0.0023 14.02 2000 0.5045 31.0910
0.0008 22.01 3000 0.5318 30.2816
0.0006 29.02 4000 0.5585 30.5989
0.0004 37.01 5000 0.5649 30.6374

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2