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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: Metformin/BART_medFineTune |
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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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# Metformin/BART_medFineTune |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.7982 |
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- Validation Loss: 0.9953 |
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- Epoch: 29 |
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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': 'WarmUp', 'config': {'initial_learning_rate': 1e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 7820, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 100, 'power': 1.0, '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 | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 2.1563 | 1.3468 | 0 | |
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| 1.4157 | 1.2090 | 1 | |
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| 1.2579 | 1.1387 | 2 | |
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| 1.1819 | 1.0888 | 3 | |
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| 1.1438 | 1.0848 | 4 | |
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| 1.0629 | 1.0512 | 5 | |
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| 1.0163 | 1.0454 | 6 | |
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| 0.9801 | 1.0248 | 7 | |
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| 0.9530 | 1.0171 | 8 | |
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| 0.9262 | 1.0108 | 9 | |
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| 0.9124 | 1.0116 | 10 | |
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| 0.8853 | 1.0043 | 11 | |
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| 0.8658 | 1.0023 | 12 | |
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| 0.8511 | 0.9987 | 13 | |
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| 0.8394 | 0.9988 | 14 | |
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| 0.8298 | 0.9994 | 15 | |
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| 0.8175 | 0.9985 | 16 | |
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| 0.8105 | 0.9936 | 17 | |
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| 0.8033 | 0.9974 | 18 | |
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| 0.8012 | 0.9948 | 19 | |
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| 0.7997 | 0.9948 | 20 | |
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| 0.7970 | 0.9957 | 21 | |
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| 0.7956 | 0.9958 | 22 | |
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| 0.8002 | 0.9954 | 23 | |
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| 0.7951 | 0.9957 | 24 | |
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| 0.7994 | 0.9948 | 25 | |
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| 0.7964 | 0.9958 | 26 | |
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| 0.7948 | 0.9957 | 27 | |
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| 0.7979 | 0.9956 | 28 | |
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| 0.7982 | 0.9953 | 29 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- TensorFlow 2.6.3 |
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- Datasets 2.0.0 |
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- Tokenizers 0.12.1 |
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