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xlm-roberta-large-qa – AI Model by Rifky | AlphaNeural AI
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Rifky
/
xlm-roberta-large-qa
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transformers
tf
bert
question-answering
generated_from_keras_callback
mit
endpoints_compatible
us
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Rifky/xlm-roberta-large-qa
This model is a fine-tuned version of
xlm-roberta-large
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 3.3813
Validation Loss: 4.1613
Epoch: 4
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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 82550, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Validation Loss
Epoch
4.3563
4.3011
0
3.9133
4.1747
1
3.7335
4.1420
2
3.5744
4.1110
3
3.3813
4.1613
4
Framework versions
Transformers 4.27.4
TensorFlow 2.12.0
Datasets 2.11.0
Tokenizers 0.13.3
