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dep-roberta – AI Model by reem442 | AlphaNeural AI
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reem442
/
dep-roberta
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transformers
tf
roberta
text-classification
generated_from_keras_callback
distilbert/distilroberta-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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reem442/dep-roberta
This model is a fine-tuned version of
distilroberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.0528
Validation Loss: 0.1076
Train Accuracy: 0.9646
Train Precision: 0.9649
Train Recall: 0.9646
Train F1: 0.9646
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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6990, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Validation Loss
Train Accuracy
Train Precision
Train Recall
Train F1
Epoch
0.1805
0.0996
0.9650
0.9650
0.9650
0.9650
0
0.0925
0.1168
0.9551
0.9569
0.9551
0.9551
1
0.0528
0.1076
0.9646
0.9649
0.9646
0.9646
2
Framework versions
Transformers 4.38.2
TensorFlow 2.15.0
Datasets 2.18.0
Tokenizers 0.15.2
