---
license: apache-2.0
tags:
- generated_from_keras_callback
base_model: google-bert/bert-base-multilingual-cased
model-index:
- name: MindAid_Diagnosis_bert-base-multilingual-cased
  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. -->

# MindAid_Diagnosis_bert-base-multilingual-cased

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4021
- Train Sparse Categorical Accuracy: 0.8656
- Validation Loss: 0.4619
- Validation Sparse Categorical Accuracy: 0.8382
- Epoch: 2

## 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': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.5668     | 0.7988                            | 0.5304          | 0.8254                                 | 0     |
| 0.4556     | 0.8425                            | 0.4576          | 0.8537                                 | 1     |
| 0.4021     | 0.8656                            | 0.4619          | 0.8382                                 | 2     |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.19.2
- Tokenizers 0.19.1