Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
tf_disilbert – AI Model by veriga | AlphaNeural AI
You can deploy this model and start earning money today!
veriga
/
tf_disilbert
like
0
transformers
tf
bert
text-classification
generated_from_keras_callback
veriga/distilbert-base-uncased-finetuned-cola
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
veriga
This model is a fine-tuned version of
veriga/distilbert-base-uncased-finetuned-cola
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 1.9335
Train Sparse Categorical Accuracy: 0.4537
Validation Loss: 1.9743
Validation Sparse Categorical Accuracy: 0.4488
Epoch: 2
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:
optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Train Sparse Categorical Accuracy
Validation Loss
Validation Sparse Categorical Accuracy
Epoch
1.9359
0.4543
1.9947
0.4505
0
1.9330
0.4547
1.9796
0.4514
1
1.9335
0.4537
1.9743
0.4488
2
Framework versions
Transformers 4.36.2
TensorFlow 2.8.2
Datasets 2.2.2
Tokenizers 0.15.0
