Beta
Explore
Marketplace
Neural Labs
Playground
Wallet
Docs
sak – AI Model by rsaketh02 | AlphaNeural AI
You can deploy this model and start earning money today!
rsaketh02
/
sak
like
0
transformers
tf
distilbert
token-classification
generated_from_keras_callback
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
rsaketh02/sak
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.0263
Validation Loss: 0.0494
Train Precision: 0.9302
Train Recall: 0.9394
Train F1: 0.9348
Train Accuracy: 0.9873
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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2631, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32
Training results
Train Loss
Validation Loss
Train Precision
Train Recall
Train F1
Train Accuracy
Epoch
0.1686
0.0562
0.9098
0.9256
0.9177
0.9842
0
0.0418
0.0494
0.9270
0.9362
0.9316
0.9866
1
0.0263
0.0494
0.9302
0.9394
0.9348
0.9873
2
Framework versions
Transformers 4.35.2
TensorFlow 2.15.0
Datasets 2.16.1
Tokenizers 0.15.0
