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---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert1010_lrate7.5b32
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. -->
# multibert1010_lrate7.5b32
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: 0.5515
- Precisions: 0.8551
- Recall: 0.8069
- F-measure: 0.8283
- Accuracy: 0.9171
## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6054 | 1.0 | 118 | 0.4021 | 0.8661 | 0.6558 | 0.6767 | 0.8698 |
| 0.316 | 2.0 | 236 | 0.4039 | 0.8167 | 0.6935 | 0.7317 | 0.8800 |
| 0.1896 | 3.0 | 354 | 0.3480 | 0.8183 | 0.7792 | 0.7780 | 0.9003 |
| 0.1318 | 4.0 | 472 | 0.3930 | 0.8529 | 0.7703 | 0.7983 | 0.8965 |
| 0.0846 | 5.0 | 590 | 0.4027 | 0.8348 | 0.8010 | 0.8141 | 0.9047 |
| 0.0652 | 6.0 | 708 | 0.4824 | 0.8298 | 0.7555 | 0.7855 | 0.9002 |
| 0.0398 | 7.0 | 826 | 0.5446 | 0.8697 | 0.7766 | 0.8110 | 0.9017 |
| 0.0335 | 8.0 | 944 | 0.4761 | 0.8402 | 0.8013 | 0.8192 | 0.9054 |
| 0.0228 | 9.0 | 1062 | 0.5232 | 0.8547 | 0.7921 | 0.8156 | 0.9085 |
| 0.0181 | 10.0 | 1180 | 0.5477 | 0.8560 | 0.7968 | 0.8226 | 0.9133 |
| 0.0106 | 11.0 | 1298 | 0.5207 | 0.8370 | 0.8050 | 0.8199 | 0.9142 |
| 0.0075 | 12.0 | 1416 | 0.5381 | 0.8469 | 0.8025 | 0.8229 | 0.9156 |
| 0.0038 | 13.0 | 1534 | 0.5573 | 0.8538 | 0.8061 | 0.8269 | 0.9165 |
| 0.0047 | 14.0 | 1652 | 0.5515 | 0.8551 | 0.8069 | 0.8283 | 0.9171 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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