Beta
Explore
Marketplace
Neural Labs
Playground
Wallet
Docs
whisper-small-ms – AI Model by Scrya | AlphaNeural AI
You can deploy this model and start earning money today!
Scrya
/
whisper-small-ms
like
0
transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
whisper-event
incomplete
generated_from_trainer
ms
google/fleurs
apache-2.0
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
Whisper Small MS - FLEURS
This model is a fine-tuned version of
openai/whisper-small
on the FLEURS dataset. It achieves the following results on the evaluation set:
eval_loss: 0.3324
eval_wer: 15.6453
eval_runtime: 347.6066
eval_samples_per_second: 2.155
eval_steps_per_second: 0.27
epoch: 10.75
step: 1000
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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2
