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EmoraBert5 – AI Model by Q317 | AlphaNeural AI
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Q317
/
EmoraBert5
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transformers
tf
roberta
text-classification
generated_from_keras_callback
wonrax/phobert-base-vietnamese-sentiment
finetune
mit
autotrain_compatible
endpoints_compatible
us
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Q317/EmoraBert5
This model is a fine-tuned version of
wonrax/phobert-base-vietnamese-sentiment
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.2081
Validation Loss: 1.0078
Train Accuracy: 0.7157
Epoch: 5
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': 86940, '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
Epoch
0.7862
0.7106
0.7007
0
0.6184
0.7058
0.7120
1
0.4890
0.7070
0.7164
2
0.3767
0.8365
0.7118
3
0.2774
0.8987
0.7189
4
0.2081
1.0078
0.7157
5
Framework versions
Transformers 4.33.1
TensorFlow 2.13.0
Datasets 2.14.5
Tokenizers 0.13.3
