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jk-finance – AI Model by jahnavikalyani | AlphaNeural AI
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jahnavikalyani
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jk-finance
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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jk-finance
This model is a fine-tuned version of
openai/whisper-small.en
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0154
Wer: 1.1611
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
Wer
0.0001
142.86
1000
0.0154
1.1611
0.0001
285.71
2000
0.0154
1.1611
0.0001
428.57
3000
0.0154
1.1611
0.0001
571.43
4000
0.0154
1.1611
Framework versions
Transformers 4.28.0
Pytorch 2.0.1+cu117
Datasets 2.13.1
Tokenizers 0.13.3
