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wav2vec-commonvoice-1 – AI Model by aman-batazia | AlphaNeural AI
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wav2vec-commonvoice-1
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transformers
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
common_voice_17_0
facebook/w2v-bert-2.0
finetune
mit
model-index
endpoints_compatible
us
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wav2vec-commonvoice-1
This model is a fine-tuned version of
facebook/w2v-bert-2.0
on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
Loss: inf
Wer: 0.2990
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: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
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
0.6465
1.0
918
inf
0.1938
0.5151
2.0
1836
inf
0.2995
0.5589
3.0
2754
inf
0.3003
0.5585
4.0
3672
inf
0.2999
0.5593
5.0
4590
inf
0.2990
Framework versions
Transformers 4.48.0
Pytorch 2.4.1+cu121
Datasets 3.6.0
Tokenizers 0.21.1
