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wav2vec2-base-librispeech-demo – AI Model by jalal2386 | AlphaNeural AI
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wav2vec2-base-librispeech-demo
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transformers
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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wav2vec2-base-librispeech-demo
This model is a fine-tuned version of
facebook/wav2vec2-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 4.0539
Wer: 0.9901
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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 10
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
15.0184
10.0
50
4.0539
0.9901
Framework versions
Transformers 5.12.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
