---
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