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scibert-ft-ner – AI Model by judithrosell | AlphaNeural AI
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judithrosell
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scibert-ft-ner
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transformers
tf
bert
token-classification
generated_from_keras_callback
allenai/scibert_scivocab_uncased
finetune
autotrain_compatible
endpoints_compatible
us
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judithrosell/scibert-ft-ner
This model is a fine-tuned version of
allenai/scibert_scivocab_uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.0543
Validation Loss: 0.2919
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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 23335, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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
0.3068
0.2466
0
0.1523
0.2540
1
0.1035
0.2643
2
0.0728
0.2701
3
0.0543
0.2919
4
Framework versions
Transformers 4.34.0
TensorFlow 2.13.0
Datasets 2.14.5
Tokenizers 0.14.1
