metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: whisper-small-af-ZA
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: PolyAI/minds14
          type: PolyAI/minds14
          config: af_za
          split: train+validation
          args: af_za
        metrics:
          - name: Wer
            type: wer
            value: 0.02925243770314193

whisper-small-af-ZA

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

Loss: 0.0415
Wer Ortho: 0.0529
Wer: 0.0293

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: 5
training_steps: 700
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0054	1.45	100	0.0312	0.0449	0.0228
0.0025	2.9	200	0.0345	0.0456	0.0231
0.0021	4.35	300	0.0325	0.0445	0.0206
0.0018	5.8	400	0.0325	0.0449	0.0202
0.0033	7.25	500	0.0390	0.0905	0.0654
0.0043	8.7	600	0.0415	0.0577	0.0347
0.0026	10.14	700	0.0415	0.0529	0.0293

Framework versions

Transformers 4.38.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1