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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Metformin/BART_medFineTune
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Metformin/BART_medFineTune
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7982
- Validation Loss: 0.9953
- Epoch: 29
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- 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}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.1563 | 1.3468 | 0 |
| 1.4157 | 1.2090 | 1 |
| 1.2579 | 1.1387 | 2 |
| 1.1819 | 1.0888 | 3 |
| 1.1438 | 1.0848 | 4 |
| 1.0629 | 1.0512 | 5 |
| 1.0163 | 1.0454 | 6 |
| 0.9801 | 1.0248 | 7 |
| 0.9530 | 1.0171 | 8 |
| 0.9262 | 1.0108 | 9 |
| 0.9124 | 1.0116 | 10 |
| 0.8853 | 1.0043 | 11 |
| 0.8658 | 1.0023 | 12 |
| 0.8511 | 0.9987 | 13 |
| 0.8394 | 0.9988 | 14 |
| 0.8298 | 0.9994 | 15 |
| 0.8175 | 0.9985 | 16 |
| 0.8105 | 0.9936 | 17 |
| 0.8033 | 0.9974 | 18 |
| 0.8012 | 0.9948 | 19 |
| 0.7997 | 0.9948 | 20 |
| 0.7970 | 0.9957 | 21 |
| 0.7956 | 0.9958 | 22 |
| 0.8002 | 0.9954 | 23 |
| 0.7951 | 0.9957 | 24 |
| 0.7994 | 0.9948 | 25 |
| 0.7964 | 0.9958 | 26 |
| 0.7948 | 0.9957 | 27 |
| 0.7979 | 0.9956 | 28 |
| 0.7982 | 0.9953 | 29 |
### Framework versions
- Transformers 4.18.0
- TensorFlow 2.6.3
- Datasets 2.0.0
- Tokenizers 0.12.1
|