whisper-small-vt / README.md
Rashmi21's picture
End of training
152aa48 verified
metadata
language:
  - dv
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - vtdataset
metrics:
  - wer
model-index:
  - name: Whisper Small vd - Rashmi Shinde
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: videos data
          type: vtdataset
        metrics:
          - name: Wer
            type: wer
            value: 11.392999765092789

Whisper Small vd - Rashmi Shinde

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

  • Loss: 0.5692
  • Wer Ortho: 14.7630
  • Wer: 11.3930

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.0002 50.0 500 0.5692 14.7630 11.3930

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1