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Transcriber-Medium – AI Model by mediaProcessing | AlphaNeural AI
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mediaProcessing
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Transcriber-Medium
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
dataset_whisper
openai/whisper-tiny
finetune
apache-2.0
model-index
endpoints_compatible
us
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Transcriber-Medium
This model is a fine-tuned version of
openai/whisper-tiny
on the dataset_whisper dataset. It achieves the following results on the evaluation set:
Loss: 2.9360
Wer: 108.5203
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: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
training_steps: 100
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
2.7536
4.02
100
2.9360
108.5203
Framework versions
Transformers 4.32.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.14.1
Tokenizers 0.13.3
