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whisper-medium-en – AI Model by JoeTan | AlphaNeural AI
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JoeTan
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whisper-medium-en
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
joetan/ep15
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-medium-fine-tuned-ep15
This model is a fine-tuned version of
openai/whisper-medium
on the ep15 dataset. It achieves the following results on the evaluation set:
Loss: 3.3931
Wer: 90.8397
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: 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: 200
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0
100.0
100
3.2156
90.8397
0.0
200.0
200
3.3931
90.8397
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1
