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---
license: apache-2.0
base_model: google/mobilebert-uncased
tags:
- generated_from_keras_callback
model-index:
- name: medmcqa-mobile-bert-uncased
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. -->
# medmcqa-mobile-bert-uncased
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on a MedMCQA dataset.
It achieves the following results on the evaluation set:
- Train Loss: 4.0974
- Validation Loss: 1.5722
- Train Accuracy: 0.244
- Epoch: 9
## 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': '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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 5000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 4852.5933 | 15.4345 | 0.245 | 0 |
| 168.1700 | 10.9270 | 0.27 | 1 |
| 103.5470 | 29.7673 | 0.243 | 2 |
| 95.7810 | 15.3191 | 0.268 | 3 |
| 62.5387 | 5.4845 | 0.262 | 4 |
| 43.1666 | 9.3354 | 0.239 | 5 |
| 32.7722 | 27.9195 | 0.24 | 6 |
| 25.1578 | 5.1954 | 0.228 | 7 |
| 12.7365 | 2.1180 | 0.219 | 8 |
| 4.0974 | 1.5722 | 0.244 | 9 |
### Framework versions
- Transformers 4.37.2
- TensorFlow 2.15.0
- Datasets 2.17.1
- Tokenizers 0.15.2
|