Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
google-bert-base-uncased-english-fp16-allagree – AI Model by Qanadil | AlphaNeural AI
You can deploy this model and start earning money today!
Qanadil
/
google-bert-base-uncased-english-fp16-allagree
like
0
transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
google-bert-base-uncased-english-fp16-allagree
This model is a fine-tuned version of
google-bert/bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1134
Accuracy: 0.9736
Precision: 0.9743
Recall: 0.9736
F1: 0.9737
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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
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_ratio: 0.3
num_epochs: 10
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.767
3.3448
50
0.4159
0.7930
0.8585
0.7930
0.7368
0.1906
6.6897
100
0.1134
0.9736
0.9743
0.9736
0.9737
Framework versions
Transformers 4.48.2
Pytorch 2.6.0+cu124
Datasets 3.3.1
Tokenizers 0.21.0
