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---
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
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