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whisper-medium-th-cv12 – AI Model by wish6424 | AlphaNeural AI
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whisper-medium-th-cv12
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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whisper-medium-th-cv12
This model is a fine-tuned version of
biodatlab/whisper-medium-th-combined-v2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3122
Wer: 23.0133
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: 6.25e-06
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: 25
training_steps: 250
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.8675
0.41
50
0.8984
28.2734
0.2598
0.82
100
0.3498
25.4960
0.1256
1.23
150
0.3226
24.8385
0.1198
1.64
200
0.3162
23.7955
0.1032
2.05
250
0.3122
23.0133
Framework versions
Transformers 4.30.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.12.1.dev0
Tokenizers 0.13.3
