metadata

license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: whisper-small-af-ZA
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: af_za
          split: train+validation
          args: af_za
        metrics:
          - name: Wer
            type: wer
            value: 0.36644093303235514

whisper-small-af-ZA

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

Loss: 0.5728
Wer: 0.3664
Wer Ortho: 0.3943

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: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Wer Ortho
0.7731	1.45	100	0.7280	0.3740	0.3863
0.2103	2.9	200	0.5116	0.3661	0.3859
0.0633	4.35	300	0.4967	0.2810	0.3008
0.0249	5.8	400	0.5003	0.3299	0.3477
0.0143	7.25	500	0.5191	0.3510	0.3660
0.0053	8.7	600	0.5149	0.3070	0.3221
0.0035	10.14	700	0.5345	0.3266	0.3443
0.0027	11.59	800	0.5339	0.3175	0.3344
0.0026	13.04	900	0.5435	0.3134	0.3328
0.0037	14.49	1000	0.5346	0.2506	0.2714
0.0045	15.94	1100	0.5438	0.3220	0.3389
0.0028	17.39	1200	0.5588	0.2551	0.2740
0.0036	18.84	1300	0.5466	0.2728	0.2702
0.0035	20.29	1400	0.5364	0.3119	0.3332
0.0056	21.74	1500	0.5608	0.2506	0.2721
0.0037	23.19	1600	0.5443	0.2833	0.3027
0.0035	24.64	1700	0.5466	0.3631	0.3866
0.0024	26.09	1800	0.5628	0.3198	0.3416
0.0036	27.54	1900	0.5495	0.2946	0.3122
0.0016	28.99	2000	0.5728	0.3664	0.3943

Framework versions

Transformers 4.31.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.4.0
Tokenizers 0.12.1