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distilbert-base-uncased-finetuned-dapt-ner-ai_data – AI Model by silviacamplani | AlphaNeural AI
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silviacamplani
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distilbert-base-uncased-finetuned-dapt-ner-ai_data
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transformers
tf
tensorboard
distilbert
token-classification
generated_from_keras_callback
apache-2.0
autotrain_compatible
endpoints_compatible
us
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silviacamplani/distilbert-base-uncased-finetuned-dapt-ner-ai_data
This model is a fine-tuned version of
silviacamplani/distilbert-base-uncased-finetuned-ai_data
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 2.3549
Validation Loss: 2.3081
Train Precision: 0.0
Train Recall: 0.0
Train F1: 0.0
Train Accuracy: 0.6392
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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 18, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Train Precision
Train Recall
Train F1
Train Accuracy
Epoch
3.0905
2.8512
0.0
0.0
0.0
0.6376
0
2.6612
2.4783
0.0
0.0
0.0
0.6392
1
2.3549
2.3081
0.0
0.0
0.0
0.6392
2
Framework versions
Transformers 4.20.1
TensorFlow 2.6.4
Datasets 2.1.0
Tokenizers 0.12.1
