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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_seed37_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_seed37_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: 0.3744
- Precisions: 0.8548
- Recall: 0.8200
- F-measure: 0.8358
- Accuracy: 0.9371
## 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: 37
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4464 | 1.0 | 236 | 0.2769 | 0.8836 | 0.7193 | 0.7495 | 0.9197 |
| 0.2278 | 2.0 | 472 | 0.2576 | 0.8850 | 0.7524 | 0.7965 | 0.9296 |
| 0.1314 | 3.0 | 708 | 0.3066 | 0.8740 | 0.7725 | 0.8059 | 0.9284 |
| 0.0964 | 4.0 | 944 | 0.3072 | 0.8267 | 0.7989 | 0.8054 | 0.9311 |
| 0.0612 | 5.0 | 1180 | 0.3229 | 0.8601 | 0.8044 | 0.8297 | 0.9340 |
| 0.0446 | 6.0 | 1416 | 0.3647 | 0.8433 | 0.7686 | 0.7952 | 0.9320 |
| 0.0319 | 7.0 | 1652 | 0.3744 | 0.8548 | 0.8200 | 0.8358 | 0.9371 |
| 0.0192 | 8.0 | 1888 | 0.4170 | 0.8724 | 0.7854 | 0.8176 | 0.9359 |
| 0.0132 | 9.0 | 2124 | 0.3994 | 0.8723 | 0.7887 | 0.8178 | 0.9371 |
| 0.0099 | 10.0 | 2360 | 0.4482 | 0.8750 | 0.8026 | 0.8327 | 0.9373 |
| 0.005 | 11.0 | 2596 | 0.4510 | 0.8731 | 0.7887 | 0.8244 | 0.9371 |
| 0.0024 | 12.0 | 2832 | 0.4455 | 0.8543 | 0.7969 | 0.8210 | 0.9373 |
| 0.0016 | 13.0 | 3068 | 0.4603 | 0.8742 | 0.8062 | 0.8355 | 0.9395 |
| 0.0018 | 14.0 | 3304 | 0.4660 | 0.8729 | 0.7996 | 0.8306 | 0.9393 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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