Jungwonchang
/

whisper_medium.en-Full-SPGIspeech-xs

Automatic Speech Recognition

Generated from Trainer

Inference Endpoints

Model card Files Files and versions Community

openai/whisper-medium.en, all the parameters updated for 5 epochs

This model is a fine-tuned version of openai/whisper-medium.en on the 2 hour dataset of SPGIspeech(custom dataset) dataset.

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: 32
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 120
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.36.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.4.0
Tokenizers 0.15.0

Downloads last month: 25

Safetensors

Model size

764M params

Tensor type

F32

·

Inference Examples

Automatic Speech Recognition

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 Jungwonchang/whisper_medium.en-Full-SPGIspeech-xs

Base model

openai/whisper-medium.en

Finetuned

(23)

this model

Evaluation results

WER on Test set for spgispeech
test set self-reported

6.670
CER on Test set for spgispeech
test set self-reported

1.980

View on Papers With Code