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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_BIES |
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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_BIES |
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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: 0.6887 |
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- Train Accuracy: 0.4877 |
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- Validation Loss: 0.7630 |
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- Validation Accuracy: 0.4497 |
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- Epoch: 5 |
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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': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 700, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 500, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, '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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| 1.7487 | 0.2210 | 1.1266 | 0.3799 | 0 | |
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| 1.0173 | 0.4225 | 0.8678 | 0.4285 | 1 | |
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| 0.8657 | 0.4491 | 0.8170 | 0.4334 | 2 | |
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| 0.7807 | 0.4664 | 0.7785 | 0.4459 | 3 | |
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| 0.7304 | 0.4708 | 0.7662 | 0.4485 | 4 | |
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| 0.6887 | 0.4877 | 0.7630 | 0.4497 | 5 | |
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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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