Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
w2v-bert-2.0_dyula – AI Model by FarmerlineML | AlphaNeural AI
You can deploy this model and start earning money today!
FarmerlineML
/
w2v-bert-2.0_dyula
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_dyula
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: 0.1112
eval_cer: 0.0312
eval_wer: 0.1146
eval_runtime: 34.6853
eval_samples_per_second: 17.385
eval_steps_per_second: 2.191
epoch: 1.9430
step: 3000
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: 2e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
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: 800
num_epochs: 32
mixed_precision_training: Native AMP
Framework versions
Transformers 4.55.2
Pytorch 2.6.0+cu124
Datasets 2.14.5
Tokenizers 0.21.4
