whisper_medium

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

  • Loss: 1.6505
  • Cer: 12.0457
  • Wer: 29.9853

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-07
  • train_batch_size: 4
  • eval_batch_size: 4
  • 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: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Wer
1.6678 0.04 500 1.6505 12.0457 29.9853

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.15.0
  • Tokenizers 0.15.0
Downloads last month
27
Safetensors
Model size
764M 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 freshpearYoon/medium2

Finetuned
(498)
this model