Whisper Medium English - Chee Li

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

  • Loss: 0.3285
  • Wer: 7.1528

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
0.005 5.3191 1000 0.2599 6.9576
0.0002 10.6383 2000 0.3051 7.1946
0.0001 15.9574 3000 0.3228 7.2295
0.0001 21.2766 4000 0.3285 7.1528

Framework versions

  • Transformers 4.43.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
Downloads last month
15
Safetensors
Model size
764M params
Tensor type
F32
·
Inference API
Unable to determine this model's library. Check the docs .

Model tree for CheeLi03/whisper-medium-en

Finetuned
(478)
this model

Evaluation results