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whisper-base-hi – AI Model by mmusawarbaig | AlphaNeural AI
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whisper-base-hi
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
dailytalk
openai/whisper-base.en
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-base.en-mmb
This model is a fine-tuned version of
openai/whisper-base.en
on the dailytalk dataset. It achieves the following results on the evaluation set:
Loss: 0.1725
Wer: 10.4301
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
0.1555
0.93
1000
0.1675
10.6676
0.1267
1.87
2000
0.1613
10.3356
0.0876
2.8
3000
0.1662
10.4398
0.0544
3.74
4000
0.1725
10.4301
Framework versions
Transformers 4.37.2
Pytorch 2.2.1+cu121
Datasets 2.20.0
Tokenizers 0.15.2
