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whisper_large – AI Model by hyojin99 | AlphaNeural AI
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hyojin99
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whisper_large
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
ko
hyojin99/EBRC
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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This model is a fine-tuned version of
openai/whisper-small
on the EBRC dataset. It achieves the following results on the evaluation set:
Loss: 0.2978
Cer: 10.5708
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: 5e-05
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: 50
training_steps: 6000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
0.3829
1.0
1500
0.3817
15.4574
0.1779
2.0
3000
0.3238
13.5614
0.0732
3.0
4500
0.2954
11.2004
0.0228
4.0
6000
0.2978
10.5708
Framework versions
Transformers 4.42.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
