README.md

metadata

language:
  - ka
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - whisper
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_1
metrics:
  - wer
model-index:
  - name: Whisper Tiny Ka
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice
          type: mozilla-foundation/common_voice_16_1
          config: ka
          split: test
          args: ka
        metrics:
          - name: Wer
            type: wer
            value: 100

Whisper Tiny Ka

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

• Loss: 7.6994
• Wer: 100.0

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: 0.003
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• 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: 1000
• training_steps: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
8.8508	15.38	25	7.6994	100.0

Framework versions

• Transformers 4.38.2
• Pytorch 2.0.1+cu118
• Datasets 2.17.1
• Tokenizers 0.15.2