README.md

metadata

language:
  - ml
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - thennal/imasc
metrics:
  - wer
base_model: openai/whisper-small
model-index:
  - name: Whisper Small Ml - IMaSC
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: ICFOSS Malayalam Speech Corpus
          type: thennal/imasc
          config: ml
          split: test
          args: ml
        metrics:
          - type: wer
            value: 10.945945945945947
            name: Wer

Whisper Small Ml - IMaSC

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

• Loss: 0.0244
• Wer: 10.9459
• Cer: 1.7890

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: 4000
• mixed_precision_training: Native AMP

Framework versions

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