Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
w2v-bert-2.0-bankon-colab-cv23.0 – AI Model by Ngue | AlphaNeural AI
You can deploy this model and start earning money today!
Ngue
/
w2v-bert-2.0-bankon-colab-cv23.0
like
0
transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
facebook/w2v-bert-2.0
finetune
mit
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
w2v-bert-2.0-bankon-colab-cv23.0
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:
eval_loss: 0.0487
eval_wer: 0.0486
eval_runtime: 14.219
eval_samples_per_second: 22.013
eval_steps_per_second: 2.813
epoch: 4.8600
step: 1200
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 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: 500
num_epochs: 10
mixed_precision_training: Native AMP
Framework versions
Transformers 4.56.2
Pytorch 2.8.0+cu126
Datasets 4.1.1
Tokenizers 0.22.0
