README.md

metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - KasuleTrevor/lingala_20hr
metrics:
  - wer
model-index:
  - name: whisper-ling-asr
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: KasuleTrevor/lingala_20hr
          type: KasuleTrevor/lingala_20hr
        metrics:
          - name: Wer
            type: wer
            value: 0.2979101583539804

whisper-ling-asr

This model is a fine-tuned version of openai/whisper-tiny on the KasuleTrevor/lingala_20hr dataset. It achieves the following results on the evaluation set:

• Loss: 0.4835
• Wer: 0.2979

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: linear
• lr_scheduler_warmup_steps: 50
• training_steps: 12000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3703	2.9851	1000	0.5100	0.2735
0.1487	5.9701	2000	0.4835	0.2979
0.0556	8.9552	3000	0.5050	0.2544
0.0171	11.9403	4000	0.5401	0.2370
0.0051	14.9254	5000	0.5673	0.2177

Framework versions

• Transformers 4.43.0
• Pytorch 2.4.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1