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w2v-bert-2.0-zuluMDD – AI Model by aconeil | AlphaNeural AI
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w2v-bert-2.0-zuluMDD
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transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
facebook/w2v-bert-2.0
finetune
mit
endpoints_compatible
us
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w2v-bert-2.0-zuluMDD
This model is a fine-tuned version of
facebook/w2v-bert-2.0
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.9443
Wer: 0.6667
Cer: 0.1413
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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
2.9185
3.8462
300
1.3991
0.7580
0.3175
0.18
7.6923
600
0.9443
0.6667
0.1413
Framework versions
Transformers 4.48.1
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0
