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whisper-large-v2-Ko – AI Model by byoussef | AlphaNeural AI
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whisper-large-v2-Ko
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transformers
pytorch
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ko
Bingsu/zeroth-korean
openai/whisper-large-v2
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-large-v2-Ko
This model is a fine-tuned version of
openai/whisper-large-v2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0617
Wer:
2.9
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
***** train metrics *****
epoch = 50.0
train_loss = 0.0234
train_runtime = 16:20:18.00
train_samples = 22262
train_samples_per_second = 19.042
train_steps_per_second = 0.085
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 1e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
num_devices: 7
total_train_batch_size: 224
total_eval_batch_size: 112
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
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0299
10.0
1000
0.0745
0.0447
0.0085
20.0
2000
0.0608
0.0353
0.0036
30.0
3000
0.0593
0.0302
0.0013
40.0
4000
0.0609
0.0282
0.0008
50.0
5000
0.0617
0.0290
Framework versions
Transformers 4.27.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.10.1
Tokenizers 0.13.2
