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whisper-medium-ivod-20250313-093608 – AI Model by luyotw | AlphaNeural AI
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whisper-medium-ivod-20250313-093608
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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Fine-tuned Whisper model for Legislative Yuan of Taiwan
This model is a fine-tuned version of
openai/whisper-medium
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0248
Wer: 64.9979
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: 16
eval_batch_size: 8
seed: 42
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
0.0129
1.3812
1000
0.0191
64.9028
0.008
2.7624
2000
0.0203
66.6984
0.0015
4.1436
3000
0.0230
65.4098
0.0008
5.5249
4000
0.0241
64.8500
0.0002
6.9061
5000
0.0248
64.9979
Framework versions
Transformers 4.45.2
Pytorch 2.5.1
Datasets 2.19.1
Tokenizers 0.20.1
