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sciq_roberta_model – AI Model by anuoluwa | AlphaNeural AI
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anuoluwa
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sciq_roberta_model
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transformers
tf
roberta
question-answering
generated_from_keras_callback
cc-by-4.0
endpoints_compatible
us
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anuoluwa/sciq_roberta_model
This model is a fine-tuned version of
deepset/tinyroberta-squad2
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.4149
Validation Loss: 0.6330
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': 2e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Validation Loss
Epoch
0.7745
0.6224
0
0.5424
0.6741
1
0.4149
0.6330
2
Framework versions
Transformers 4.25.1
TensorFlow 2.11.0
Datasets 2.10.0
Tokenizers 0.13.2
