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new_results-5 – AI Model by lmarchyok | AlphaNeural AI
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lmarchyok
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new_results-5
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transformers
tf
bert
fill-mask
generated_from_keras_callback
autotrain_compatible
endpoints_compatible
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lmarchyok/new_results-5
This model is a fine-tuned version of
pretrained_models/ClinicalBERT_1a/pytorch_model.bin
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 4.5153
Validation Loss: 4.4219
Epoch: 8
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': -876, '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
10.5672
8.8477
0
8.3874
7.8035
1
7.4823
6.9117
2
6.5856
5.7931
3
5.7664
5.4113
4
5.2815
5.0462
5
4.9782
4.6423
6
4.7095
4.4299
7
4.5153
4.4219
8
Framework versions
Transformers 4.26.1
TensorFlow 2.11.0
Datasets 2.13.1
Tokenizers 0.13.2
