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---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert_dataaugmentation
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# multibert_dataaugmentation
This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7138
- Precisions: 0.8609
- Recall: 0.8356
- F-measure: 0.8464
- Accuracy: 0.8989
## 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:
- learning_rate: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.5775 | 1.0 | 285 | 0.4827 | 0.7847 | 0.7040 | 0.7340 | 0.8509 |
| 0.2623 | 2.0 | 570 | 0.5829 | 0.8035 | 0.7359 | 0.7591 | 0.8613 |
| 0.1503 | 3.0 | 855 | 0.5609 | 0.7946 | 0.8083 | 0.7917 | 0.8804 |
| 0.088 | 4.0 | 1140 | 0.5481 | 0.8406 | 0.7997 | 0.8170 | 0.8860 |
| 0.0592 | 5.0 | 1425 | 0.6359 | 0.8207 | 0.8210 | 0.8120 | 0.8828 |
| 0.0414 | 6.0 | 1710 | 0.6589 | 0.8313 | 0.8171 | 0.8198 | 0.8843 |
| 0.0271 | 7.0 | 1995 | 0.7117 | 0.8689 | 0.7882 | 0.8216 | 0.8936 |
| 0.0179 | 8.0 | 2280 | 0.7138 | 0.8609 | 0.8356 | 0.8464 | 0.8989 |
| 0.0121 | 9.0 | 2565 | 0.7289 | 0.8456 | 0.8128 | 0.8278 | 0.8946 |
| 0.0081 | 10.0 | 2850 | 0.7603 | 0.8344 | 0.8223 | 0.8278 | 0.8956 |
| 0.0058 | 11.0 | 3135 | 0.8126 | 0.8576 | 0.8107 | 0.8322 | 0.8942 |
| 0.0041 | 12.0 | 3420 | 0.8004 | 0.8582 | 0.8267 | 0.8415 | 0.8955 |
| 0.0031 | 13.0 | 3705 | 0.7936 | 0.8599 | 0.8275 | 0.8426 | 0.8961 |
| 0.0028 | 14.0 | 3990 | 0.8076 | 0.8602 | 0.8226 | 0.8401 | 0.8966 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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