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hindi – AI Model by ujs | AlphaNeural AI

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ujs/
hindi

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automatic-speech-recognition

generated_from_trainer

common_voice_11_0

endpoints_compatible

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hindi

This model was trained from scratch on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

eval_loss: 0.8079
eval_wer: 0.4951
eval_runtime: 225.6871
eval_samples_per_second: 12.823
eval_steps_per_second: 1.604
epoch: 1.71
step: 1400

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: 0.0003
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 700
num_epochs: 10
mixed_precision_training: Native AMP

Framework versions

Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2