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vast_trans – AI Model by whitebemail | AlphaNeural AI

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whitebemail/
vast_trans

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vast_trans

This model is a fine-tuned version of facebook/wav2vec2-base on the timit_asr dataset. It achieves the following results on the evaluation set:

eval_loss: 0.4126
eval_cer: 0.1224
eval_runtime: 17.9127
eval_samples_per_second: 46.894
eval_steps_per_second: 5.862
epoch: 15.26
step: 3800

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: 0.0001
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: 1000
num_epochs: 25
mixed_precision_training: Native AMP

Framework versions

Transformers 4.17.0
Pytorch 2.4.0
Datasets 1.18.3
Tokenizers 0.20.3