metadata

base_model: openai/whisper-medium
library_name: transformers
license: apache-2.0
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: whisper-medium-Cantonese-fine-tune-bible-100
    results: []

whisper-medium-Cantonese-fine-tune-bible-100

This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2343
Wer: 83.6364

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: 5e-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: 5
training_steps: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0072	7.6923	100	0.2343	83.6364

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1