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--- |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: silviacamplani/distilbert-finetuned-tapt-ner-ai |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# silviacamplani/distilbert-finetuned-tapt-ner-ai |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.9093 |
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- Validation Loss: 0.9177 |
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- Train Precision: 0.3439 |
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- Train Recall: 0.3697 |
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- Train F1: 0.3563 |
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- Train Accuracy: 0.7697 |
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- Epoch: 9 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 350, '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} |
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- training_precision: mixed_float16 |
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### Training results |
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| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| |
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| 2.5750 | 1.7754 | 0.0 | 0.0 | 0.0 | 0.6480 | 0 | |
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| 1.6567 | 1.4690 | 0.0 | 0.0 | 0.0 | 0.6480 | 1 | |
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| 1.3888 | 1.2847 | 0.0 | 0.0 | 0.0 | 0.6480 | 2 | |
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| 1.2569 | 1.1744 | 0.0526 | 0.0221 | 0.0312 | 0.6751 | 3 | |
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| 1.1536 | 1.0884 | 0.2088 | 0.1704 | 0.1876 | 0.7240 | 4 | |
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| 1.0722 | 1.0281 | 0.2865 | 0.2641 | 0.2748 | 0.7431 | 5 | |
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| 1.0077 | 0.9782 | 0.3151 | 0.3135 | 0.3143 | 0.7553 | 6 | |
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| 0.9582 | 0.9437 | 0.3254 | 0.3492 | 0.3369 | 0.7661 | 7 | |
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| 0.9268 | 0.9242 | 0.3381 | 0.3595 | 0.3485 | 0.7689 | 8 | |
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| 0.9093 | 0.9177 | 0.3439 | 0.3697 | 0.3563 | 0.7697 | 9 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- TensorFlow 2.6.4 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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