whisper-medium-production – AI Model by shane062 | AlphaNeural AI

You can deploy this model and start earning money today!

shane062/
whisper-medium-production

like

0

automatic-speech-recognition

generated_from_trainer

openai/whisper-medium

endpoints_compatible

Views

No views yet

whisper-medium-production

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

Loss: 0.3373
Wer Ortho: 34.2105
Wer: 34.2105

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 30
training_steps: 300

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0296	20.0	60	0.3520	50.0	47.3684
0.0001	40.0	120	0.3399	34.2105	34.2105
0.0	60.0	180	0.3378	34.2105	34.2105
0.0	80.0	240	0.3370	34.2105	34.2105
0.0	100.0	300	0.3373	34.2105	34.2105

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1