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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: thefishtalepundit/SensemakingDetectionModel |
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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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# thefishtalepundit/SensemakingDetectionModel |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 0.1516 |
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- Validation Loss: 0.3241 |
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- Train Accuracy: 0.8872 |
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- Train Precision: 0.9065 |
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- Train Recall: 0.8926 |
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- Train F1: 0.8995 |
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- Epoch: 2 |
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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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1435, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Train Accuracy | Train Precision | Train Recall | Train F1 | Epoch | |
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|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:| |
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| 0.4231 | 0.3150 | 0.875 | 0.8872 | 0.8926 | 0.8899 | 0 | |
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| 0.2335 | 0.3034 | 0.8854 | 0.9037 | 0.8926 | 0.8981 | 1 | |
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| 0.1516 | 0.3241 | 0.8872 | 0.9065 | 0.8926 | 0.8995 | 2 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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