metadata

language:
  - en
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - speech_command_v0_02
metrics:
  - wer
model-index:
  - name: Whisper Small command - fatipd
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: speech command v02
          type: speech_command_v0_02
          config: null
          split: None
          args: 'config: hi, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 0.3861003861003861

Whisper Small command - fatipd

This model is a fine-tuned version of openai/whisper-small on the speech command v02 dataset. It achieves the following results on the evaluation set:

Loss: 0.0021
Wer: 0.3861

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
training_steps: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0095	0.2	250	0.0042	0.7239
0.0068	0.4	500	0.0051	1.0135
0.0045	0.6	750	0.0021	0.3861
0.0056	0.8	1000	0.0018	1.5927
0.0021	1.0	1250	0.0023	8.8803
0.0081	1.2	1500	0.0033	2.0270
0.0056	1.4	1750	0.0023	6.1293
0.0028	1.6	2000	0.0017	0.8687
0.0064	1.81	2250	0.0011	0.8687
0.0005	2.01	2500	0.0014	2.0270
0.0015	2.21	2750	0.0013	1.4961
0.0012	2.41	3000	0.0014	1.8822

Framework versions

Transformers 4.30.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3