metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - common_voice_17_0
metrics:
  - wer
model-index:
  - name: whisper-tiny-common_voice_17_0-id
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_17_0
          type: common_voice_17_0
          config: id
          split: None
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 0.1807044410413476

whisper-tiny-common_voice_17_0-id

This model is a fine-tuned version of openai/whisper-tiny on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.2000
Wer: 0.1807

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: 500
training_steps: 20000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4911	0.4229	1000	0.4546	0.3321
0.4078	0.8458	2000	0.3520	0.2807
0.2679	1.2688	3000	0.3050	0.2421
0.2423	1.6917	4000	0.2725	0.2217
0.169	2.1146	5000	0.2515	0.2184
0.1646	2.5375	6000	0.2377	0.2082
0.1731	2.9605	7000	0.2189	0.1911
0.1017	3.3834	8000	0.2135	0.1970
0.0985	3.8063	9000	0.2077	0.1819
0.0828	4.2292	10000	0.2070	0.1792
0.06	4.6521	11000	0.1991	0.1826
0.0629	5.0751	12000	0.2012	0.1918
0.0545	5.4980	13000	0.2017	0.1864
0.0392	5.9209	14000	0.1985	0.1910
0.0338	6.3438	15000	0.1989	0.1807
0.0312	6.7668	16000	0.1982	0.1945
0.0237	7.1897	17000	0.1998	0.1842
0.0223	7.6126	18000	0.1994	0.1800
0.0192	8.0355	19000	0.1993	0.1806
0.0158	8.4584	20000	0.2000	0.1807

Framework versions

Transformers 4.42.0.dev0
Pytorch 2.1.0
Datasets 2.19.1
Tokenizers 0.19.1