README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - Jungwonchang/spgispeech_xs
base_model: openai/whisper-medium.en
model-index:
  - name: openai/whisper-medium.en, all the parameters updated for 5 epochs
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Test set for spgispeech
          type: kensho/spgispeech
          config: test
          split: test
        metrics:
          - type: wer
            value: 6.67
            name: WER
          - type: cer
            value: 1.98
            name: CER

openai/whisper-medium.en, all the parameters updated for 5 epochs

This model is a fine-tuned version of openai/whisper-medium.en on the 2 hour dataset of SPGIspeech(custom dataset) dataset.

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: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• training_steps: 120
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.36.0.dev0
• Pytorch 1.12.1+cu116
• Datasets 2.4.0
• Tokenizers 0.15.0