README.md

metadata

language:
  - multilingual
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - abiyo27/BibleTTS_Ewe-Bible
metrics:
  - wer
model-index:
  - name: Whisper_Small_Ewe
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: BibleTTS
          type: abiyo27/BibleTTS_Ewe-Bible
          config: default
          split: None
          args: 'config: ewe, split: train'
        metrics:
          - name: Wer
            type: wer
            value: 10.094952523738131

Whisper_Small_Ewe

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

• Loss: 0.1021
• Wer: 10.0950

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: 1
• eval_batch_size: 8
• 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: 14000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2196	0.1802	4000	0.1780	19.3903
0.1587	0.3605	8000	0.1375	13.4933
0.1162	0.5407	12000	0.1021	10.0950

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.1+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1