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--- |
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license: mit |
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base_model: microsoft/mdeberta-v3-base |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: khadija69/debertav3_ASE_kgl_BIES2 |
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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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# khadija69/debertav3_ASE_kgl_BIES2 |
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This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.6418 |
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- Train Accuracy: 0.6024 |
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- Validation Loss: 0.7774 |
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- Validation Accuracy: 0.5724 |
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- Epoch: 6 |
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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': 1e-05, 'decay_steps': 4000, '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 | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 1.1865 | 0.4781 | 0.9186 | 0.5364 | 0 | |
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| 0.8841 | 0.5450 | 0.8210 | 0.5555 | 1 | |
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| 0.7972 | 0.5688 | 0.7997 | 0.5624 | 2 | |
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| 0.7395 | 0.5818 | 0.7777 | 0.5682 | 3 | |
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| 0.7011 | 0.5931 | 0.7836 | 0.5708 | 4 | |
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| 0.6760 | 0.5998 | 0.7845 | 0.5696 | 5 | |
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| 0.6418 | 0.6024 | 0.7774 | 0.5724 | 6 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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