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whisper_go – AI Model by Kiniu | AlphaNeural AI
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Kiniu
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whisper_go
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
en
Kiniu/go_dataset
apache-2.0
model-index
endpoints_compatible
us
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whisper_go
This model is a fine-tuned version of
openai/whisper-small
on the go_dataset dataset. It achieves the following results on the evaluation set:
Loss: 0.3608
Wer: 190.5437
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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
0.0369
4.71
1000
0.2629
76.9137
0.0015
9.41
2000
0.3291
110.8992
0.0018
14.12
3000
0.3530
181.1038
0.0006
18.82
4000
0.3608
190.5437
Framework versions
Transformers 4.27.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2
