---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_keras_callback
model-index:
- name: bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract
  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. -->

# bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 2.4942
- Train Categorical Accuracy: 0.0002
- Train Top 2 Categorical Accuracy: 0.0005
- Train Top 10 Categorical Accuracy: 0.0024
- Validation Loss: 3.0737
- Validation Categorical Accuracy: 0.0003
- Validation Top 2 Categorical Accuracy: 0.0006
- Validation Top 10 Categorical Accuracy: 0.0028
- Train Accuracy: 0.4846
- Epoch: 7

## 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': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 6e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 6e-05, 'decay_steps': 335420, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 500, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Categorical Accuracy | Train Top 2 Categorical Accuracy | Train Top 10 Categorical Accuracy | Validation Loss | Validation Categorical Accuracy | Validation Top 2 Categorical Accuracy | Validation Top 10 Categorical Accuracy | Train Accuracy | Epoch |
|:----------:|:--------------------------:|:--------------------------------:|:---------------------------------:|:---------------:|:-------------------------------:|:-------------------------------------:|:--------------------------------------:|:--------------:|:-----:|
| 4.8075     | 0.0001                     | 0.0002                           | 0.0020                            | 3.6686          | 0.0000                          | 0.0001                                | 0.0017                                 | 0.3839         | 0     |
| 3.4867     | 0.0002                     | 0.0004                           | 0.0028                            | 3.3360          | 0.0001                          | 0.0002                                | 0.0014                                 | 0.4337         | 1     |
| 3.1865     | 0.0002                     | 0.0004                           | 0.0027                            | 3.2005          | 0.0002                          | 0.0005                                | 0.0033                                 | 0.4556         | 2     |
| 2.9969     | 0.0002                     | 0.0005                           | 0.0027                            | 3.1379          | 0.0001                          | 0.0002                                | 0.0014                                 | 0.4675         | 3     |
| 2.8489     | 0.0002                     | 0.0004                           | 0.0025                            | 3.0900          | 0.0002                          | 0.0005                                | 0.0031                                 | 0.4746         | 4     |
| 2.7212     | 0.0002                     | 0.0005                           | 0.0025                            | 3.0744          | 0.0002                          | 0.0003                                | 0.0021                                 | 0.4799         | 5     |
| 2.6035     | 0.0002                     | 0.0004                           | 0.0025                            | 3.0660          | 0.0002                          | 0.0004                                | 0.0023                                 | 0.4831         | 6     |
| 2.4942     | 0.0002                     | 0.0005                           | 0.0024                            | 3.0737          | 0.0003                          | 0.0006                                | 0.0028                                 | 0.4846         | 7     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.13.0
- Datasets 2.15.0
- Tokenizers 0.15.0