whisper-large-odiya

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 13 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2808
  • Wer Ortho: 45.8771
  • Wer: 18.4527

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: 16
  • 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: 20
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.0019 9.71 500 0.2362 45.4898 19.3002
0.0001 19.42 1000 0.2808 45.8771 18.4527

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
Downloads last month
28
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 Apocalypse-19/whisper-large-odiya

Finetuned
(191)
this model

Dataset used to train Apocalypse-19/whisper-large-odiya

Evaluation results