Whisper Small en

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3817
  • Wer: 13.2960

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: 64
  • 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: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.2368 1.0974 1000 0.3761 14.2483
0.1107 3.0922 2000 0.4002 14.1083
0.1615 5.087 3000 0.3839 13.6105
0.0793 7.0818 4000 0.4053 13.8265
0.1457 9.0766 5000 0.3817 13.2960

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
Downloads last month
27
Safetensors
Model size
242M params
Tensor type
F32
·
Inference Examples
Unable to determine this model's library. Check the docs .

Model tree for deepdml/whisper-small-en-cv17

Finetuned
(2103)
this model

Dataset used to train deepdml/whisper-small-en-cv17

Evaluation results