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whisper-medium-as-600-32-1e-05-bn – AI Model by kpriyanshu256 | AlphaNeural AI
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whisper-medium-as-600-32-1e-05-bn
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
whisper-event
generated_from_trainer
as
mozilla-foundation/common_voice_11_0
apache-2.0
model-index
endpoints_compatible
us
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openai/whisper-medium-Assamese
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 1.0992
Wer: 58.3649
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: 2
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 600
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0841
1.13
600
1.0992
58.3649
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1
