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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: nikoslefkos/conll03_model |
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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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# nikoslefkos/conll03_model |
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This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on conll03 dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0028 |
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- Validation Loss: 0.0797 |
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- Train Precision: 0.9178 |
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- Train Recall: 0.9409 |
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- Train F1: 0.9292 |
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- Train Accuracy: 0.9840 |
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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: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 4380, '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} |
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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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| 0.2257 | 0.0909 | 0.8675 | 0.9037 | 0.8853 | 0.9733 | 0 | |
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| 0.0638 | 0.0670 | 0.9003 | 0.9266 | 0.9133 | 0.9808 | 1 | |
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| 0.0356 | 0.0668 | 0.9070 | 0.9335 | 0.9201 | 0.9818 | 2 | |
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| 0.0223 | 0.0660 | 0.9137 | 0.9334 | 0.9234 | 0.9828 | 3 | |
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| 0.0152 | 0.0750 | 0.9007 | 0.9317 | 0.9159 | 0.9805 | 4 | |
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| 0.0101 | 0.0736 | 0.9104 | 0.9371 | 0.9235 | 0.9828 | 5 | |
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| 0.0067 | 0.0740 | 0.9203 | 0.9391 | 0.9296 | 0.9838 | 6 | |
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| 0.0046 | 0.0767 | 0.9133 | 0.9379 | 0.9254 | 0.9832 | 7 | |
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| 0.0034 | 0.0806 | 0.9160 | 0.9399 | 0.9278 | 0.9837 | 8 | |
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| 0.0028 | 0.0797 | 0.9178 | 0.9409 | 0.9292 | 0.9840 | 9 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- TensorFlow 2.12.0 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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