README.md

metadata

library_name: transformers
language:
  - sw
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - DigitalUmuganda/AfriVoice
metrics:
  - wer
model-index:
  - name: Whisper Small
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: AfriVoice
          type: DigitalUmuganda/AfriVoice
          args: 'config: sw, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 37.234493658687015

Whisper Small

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

• Loss: 1.0151
• Wer: 37.2345

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
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 40
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1977	8.1301	500	0.7429	41.9683
0.0059	16.2602	1000	0.9167	38.4064
0.001	24.3902	1500	0.9849	37.3501
0.0007	32.5203	2000	1.0151	37.2345

Framework versions

• Transformers 4.44.2
• Pytorch 2.1.0+cu118
• Datasets 2.21.0
• Tokenizers 0.19.1