metadata

language:
  - hi
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Hi - Swedish
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: hi
          split: test
          args: 'config: hi, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 19.647226479524615

Whisper Small Hi - Swedish

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.3953
Wer: 19.6472

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1331	1.29	1000	0.3014	22.3602
0.0537	2.59	2000	0.2988	20.8572
0.0217	3.88	3000	0.3093	20.5641
0.004	5.17	4000	0.3551	20.0479
0.0015	6.47	5000	0.3701	20.0022
0.0015	7.76	6000	0.3769	19.7386
0.0007	9.06	7000	0.3908	19.7010
0.0006	10.35	8000	0.3953	19.6472

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.9.0+cu102
Datasets 2.7.1
Tokenizers 0.13.2