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whisper-finetune-all_0823 – AI Model by LeoKuo49 | AlphaNeural AI
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whisper-finetune-all_0823
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
zh
LeoKuo49/Amitabha_all
openai/whisper-large-v2
finetune
apache-2.0
endpoints_compatible
us
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Whisper-finetune_all
This model is a fine-tuned version of
openai/whisper-large-v2
on the Amitabha_all dataset. It achieves the following results on the evaluation set:
Loss: 0.0002
Cer: 0.1505
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: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
0.0581
3.1056
1000
0.0515
6.2281
0.0132
6.2112
2000
0.0075
2.8061
0.0009
9.3168
3000
0.0006
0.3260
0.0001
12.4224
4000
0.0002
0.1505
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
