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metadata
language:
  - en
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - jmcastelo17/FIFA_commentary
metrics:
  - wer
model-index:
  - name: Whisper Small FIFA_commentary
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: FIFA_commentary
          type: jmcastelo17/FIFA_commentary
        metrics:
          - name: Wer
            type: wer
            value: 23.003194888178914

Whisper Small FIFA_commentary

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

  • Loss: 1.3021
  • Wer: 23.0032

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: 5e-06
  • train_batch_size: 32
  • eval_batch_size: 8
  • 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
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 1.0 3 1.3065 23.6422
No log 2.0 6 1.3063 23.6422
No log 3.0 9 1.3060 23.6422
No log 4.0 12 1.3054 23.6422
No log 5.0 15 1.3047 23.6422
No log 6.0 18 1.3041 23.6422
No log 7.0 21 1.3038 23.3227
No log 8.0 24 1.3030 23.0032
No log 9.0 27 1.3025 23.0032
No log 10.0 30 1.3021 23.0032

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2