README.md

metadata

language:
  - ha
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - Seon25/common_voice_16_0_
metrics:
  - wer
model-index:
  - name: Whisper Tiny Ha - Eldad Akhaumere
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 16.0
          type: Seon25/common_voice_16_0_
          config: ha
          split: None
          args: 'config: ha, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 107.2810883310979

Whisper Tiny Ha - Eldad Akhaumere

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:

• Loss: 2.5851
• Wer Ortho: 108.4180
• Wer: 107.2811

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
• num_epochs: 15.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
1.3176	3.1847	500	2.1073	133.8086	132.4392
0.624	6.3694	1000	2.2333	110.4492	111.1324
0.2135	9.5541	1500	2.4375	101.6211	100.4407
0.0593	12.7389	2000	2.5851	108.4180	107.2811

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1