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e_results-5 – AI Model by lmarchyok | AlphaNeural AI
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lmarchyok
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e_results-5
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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-5
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: 2.3001
Validation Loss: 2.1694
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
3.1469
2.6912
0
2.7524
2.5054
1
2.6168
2.4093
2
2.5259
2.2784
3
2.4613
2.1857
4
2.3348
2.1319
5
2.2734
2.1327
6
2.2881
2.1966
7
2.2819
2.2081
8
2.3001
2.1694
9
Framework versions
Transformers 4.26.1
TensorFlow 2.11.0
Datasets 2.13.1
Tokenizers 0.13.2
