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content – AI Model by Shivangi64 | AlphaNeural AI
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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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This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3422
Wer: 0.5505
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: 240
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.1692
0.43
100
0.9226
237.4679
0.4615
0.85
200
0.3422
0.5505
Framework versions
Transformers 4.35.2
Pytorch 1.13.1+cu117
Datasets 2.15.0
Tokenizers 0.15.0
