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e_results-10 – AI Model by lmarchyok | AlphaNeural AI
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lmarchyok
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e_results-10
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transformers
tf
bert
fill-mask
generated_from_keras_callback
apache-2.0
autotrain_compatible
endpoints_compatible
us
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lmarchyok/e_results-10
This model is a fine-tuned version of
bert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 2.2988
Validation Loss: 2.1642
Epoch: 9
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': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -850, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '
passive_serialization
': True}, 'warmup_steps': 1000, 'power': 1.0, '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: mixed_float16
Training results
Train Loss
Validation Loss
Epoch
3.1258
2.6586
0
2.7287
2.4807
1
2.6006
2.3940
2
2.5067
2.2871
3
2.4428
2.2827
4
2.3593
2.1923
5
2.3269
2.2088
6
2.2879
2.1612
7
2.2847
2.1540
8
2.2988
2.1642
9
Framework versions
Transformers 4.26.1
TensorFlow 2.11.0
Datasets 2.13.1
Tokenizers 0.13.2
