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whisper-small-ivod-round2 – AI Model by luyotw | AlphaNeural AI
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whisper-small-ivod-round2
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
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-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0250
Wer: 70.3375
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
0.0169
1.0730
1000
0.0213
69.0134
0.0082
2.1459
2000
0.0217
68.5774
0.0073
3.2189
3000
0.0230
69.4332
0.0042
4.2918
4000
0.0244
70.5474
0.0034
5.3648
5000
0.0250
70.3375
Framework versions
Transformers 4.45.2
Pytorch 2.5.1
Datasets 2.19.1
Tokenizers 0.20.1
