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asr-til-wav2vec – AI Model by Aadithyak | AlphaNeural AI
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Aadithyak
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asr-til-wav2vec
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transformers
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
facebook/wav2vec2-base-960h
finetune
apache-2.0
endpoints_compatible
us
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wav2vec2-finetuned-til
This model is a fine-tuned version of
facebook/wav2vec2-base-960h
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 40297.4414
eval_wer: 1.0382
eval_runtime: 64.3538
eval_samples_per_second: 6.993
eval_steps_per_second: 1.165
epoch: 3.7467
step: 630
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: 5e-05
train_batch_size: 6
eval_batch_size: 6
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 24
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 6
mixed_precision_training: Native AMP
Framework versions
Transformers 4.51.3
Pytorch 2.5.1+cu121
Datasets 3.6.0
Tokenizers 0.21.1