Visualize in Weights & Biases

Whisper Small Hi

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: 0.4390
  • Wer: 32.4854

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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0922 2.4450 1000 0.2977 35.0038
0.0209 4.8900 2000 0.3548 34.0430
0.0013 7.3350 3000 0.4121 32.3584
0.0004 9.7800 4000 0.4390 32.4854

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3
Downloads last month
18
Safetensors
Model size
242M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for neuronbit/whisper-small-hi-test

Finetuned
(2194)
this model

Dataset used to train neuronbit/whisper-small-hi-test

Evaluation results