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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Sidziesama/Legal_NER_Support_Model_distilledbert |
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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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# Sidziesama/Legal_NER_Support_Model_distilledbert |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0582 |
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- Validation Loss: 0.0980 |
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- Train Precision: 0.7952 |
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- Train Recall: 0.8552 |
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- Train F1: 0.8241 |
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- Train Accuracy: 0.9716 |
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- Epoch: 4 |
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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: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3435, '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} |
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- training_precision: float32 |
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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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| 0.4207 | 0.1608 | 0.6623 | 0.7498 | 0.7034 | 0.9557 | 0 | |
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| 0.1304 | 0.1118 | 0.7580 | 0.8116 | 0.7839 | 0.9668 | 1 | |
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| 0.0891 | 0.1012 | 0.7698 | 0.8525 | 0.8090 | 0.9701 | 2 | |
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| 0.0699 | 0.0976 | 0.7933 | 0.8507 | 0.8210 | 0.9713 | 3 | |
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| 0.0582 | 0.0980 | 0.7952 | 0.8552 | 0.8241 | 0.9716 | 4 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- TensorFlow 2.15.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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