metadata

language:
  - sv
license: apache-2.0
base_model: openai/whisper-small
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
  - google/fleurs
metrics:
  - wer
model-index:
  - name: whisper-small-sv-extra-data
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_13_0
          type: mozilla-foundation/common_voice_13_0
          config: default
          split: test
          args: 'config: sv, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 22.158468913970783
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
        metrics:
          - name: Wer
            type: wer
            value: 22.158468913970783

whisper-small-sv-extra-data

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 and the google/fleurs datasets. It achieves the following results on the evaluation set:

Loss: 0.3843
Wer: 22.1585

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: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3189	0.53	500	0.3610	25.2029
0.1451	1.05	1000	0.3337	23.6495
0.1432	1.58	1500	0.3263	22.8908
0.0572	2.1	2000	0.3284	22.1622
0.0502	2.63	2500	0.3405	22.2000
0.0259	3.15	3000	0.3596	22.1924
0.0246	3.68	3500	0.3650	22.2208
0.0137	4.2	4000	0.3843	22.1585

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.1+cu118
Datasets 2.15.0
Tokenizers 0.15.0