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wave2vecWvald11 – AI Model by AAK1423 | AlphaNeural AI
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AAK1423
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wave2vecWvald11
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transformers
tensorboard
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
facebook/wav2vec2-xls-r-300m
finetune
apache-2.0
endpoints_compatible
us
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wave2vecWvald11
This model is a fine-tuned version of
facebook/wav2vec2-xls-r-300m
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2007
Wer: 0.2388
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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 500
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
7.643
3.8878
400
1.3868
0.9857
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
