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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_seed33_1311
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_seed33_1311
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: 0.4996
- Precisions: 0.8590
- Recall: 0.8170
- F-measure: 0.8353
- Accuracy: 0.9359
## 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: 33
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4674 | 1.0 | 236 | 0.2914 | 0.8891 | 0.6852 | 0.7119 | 0.9125 |
| 0.2266 | 2.0 | 472 | 0.2489 | 0.8410 | 0.7811 | 0.8044 | 0.9294 |
| 0.1394 | 3.0 | 708 | 0.2650 | 0.8611 | 0.7777 | 0.7929 | 0.9296 |
| 0.0878 | 4.0 | 944 | 0.2721 | 0.8608 | 0.8165 | 0.8324 | 0.9373 |
| 0.06 | 5.0 | 1180 | 0.3164 | 0.8457 | 0.7877 | 0.8105 | 0.9342 |
| 0.0378 | 6.0 | 1416 | 0.3793 | 0.8788 | 0.7972 | 0.8309 | 0.9335 |
| 0.0285 | 7.0 | 1652 | 0.3807 | 0.8665 | 0.7905 | 0.8233 | 0.9299 |
| 0.0153 | 8.0 | 1888 | 0.4636 | 0.8555 | 0.7855 | 0.8152 | 0.9303 |
| 0.0115 | 9.0 | 2124 | 0.4649 | 0.8336 | 0.8135 | 0.8190 | 0.9337 |
| 0.0064 | 10.0 | 2360 | 0.5120 | 0.8522 | 0.8010 | 0.8219 | 0.9325 |
| 0.0052 | 11.0 | 2596 | 0.5008 | 0.8616 | 0.8034 | 0.8288 | 0.9337 |
| 0.0038 | 12.0 | 2832 | 0.4807 | 0.8616 | 0.8133 | 0.8346 | 0.9354 |
| 0.0016 | 13.0 | 3068 | 0.4995 | 0.8514 | 0.8186 | 0.8322 | 0.9359 |
| 0.0012 | 14.0 | 3304 | 0.4996 | 0.8590 | 0.8170 | 0.8353 | 0.9359 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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