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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_seed34_1611
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_seed34_1611
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: 0.4810
- Precisions: 0.8743
- Recall: 0.8016
- F-measure: 0.8318
- Accuracy: 0.9364
## 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: 34
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4954 | 1.0 | 236 | 0.2579 | 0.8908 | 0.7174 | 0.7485 | 0.9181 |
| 0.2427 | 2.0 | 472 | 0.2589 | 0.8472 | 0.7340 | 0.7497 | 0.9209 |
| 0.1427 | 3.0 | 708 | 0.2844 | 0.8461 | 0.7830 | 0.8096 | 0.9325 |
| 0.0916 | 4.0 | 944 | 0.3453 | 0.8497 | 0.7804 | 0.8122 | 0.9306 |
| 0.0616 | 5.0 | 1180 | 0.3281 | 0.8500 | 0.7936 | 0.8160 | 0.9303 |
| 0.0414 | 6.0 | 1416 | 0.3859 | 0.8494 | 0.7930 | 0.8167 | 0.9337 |
| 0.0272 | 7.0 | 1652 | 0.3863 | 0.8572 | 0.7894 | 0.8167 | 0.9323 |
| 0.0207 | 8.0 | 1888 | 0.3998 | 0.8525 | 0.7938 | 0.8195 | 0.9337 |
| 0.0117 | 9.0 | 2124 | 0.4348 | 0.8555 | 0.7983 | 0.8228 | 0.9330 |
| 0.0089 | 10.0 | 2360 | 0.4858 | 0.8699 | 0.7708 | 0.7996 | 0.9294 |
| 0.0054 | 11.0 | 2596 | 0.4676 | 0.8559 | 0.7959 | 0.8197 | 0.9344 |
| 0.0036 | 12.0 | 2832 | 0.4582 | 0.8665 | 0.8038 | 0.8291 | 0.9364 |
| 0.0025 | 13.0 | 3068 | 0.4810 | 0.8743 | 0.8016 | 0.8318 | 0.9364 |
| 0.0018 | 14.0 | 3304 | 0.4801 | 0.8685 | 0.8036 | 0.8309 | 0.9366 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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