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---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: multibert1110_lrate7.5b8
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. -->
# multibert1110_lrate7.5b8
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: 0.6124
- Precisions: 0.8795
- Recall: 0.7898
- F-measure: 0.8228
- Accuracy: 0.9026
## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6395 | 1.0 | 471 | 0.4532 | 0.8345 | 0.6789 | 0.6899 | 0.8619 |
| 0.3636 | 2.0 | 942 | 0.3956 | 0.8284 | 0.7491 | 0.7766 | 0.8853 |
| 0.2471 | 3.0 | 1413 | 0.5037 | 0.8053 | 0.6950 | 0.7258 | 0.8821 |
| 0.1785 | 4.0 | 1884 | 0.5098 | 0.8444 | 0.7522 | 0.7755 | 0.8936 |
| 0.1279 | 5.0 | 2355 | 0.5574 | 0.8751 | 0.7735 | 0.8077 | 0.8973 |
| 0.097 | 6.0 | 2826 | 0.6124 | 0.8795 | 0.7898 | 0.8228 | 0.9026 |
| 0.071 | 7.0 | 3297 | 0.5377 | 0.8621 | 0.7836 | 0.8157 | 0.9044 |
| 0.0494 | 8.0 | 3768 | 0.5842 | 0.8705 | 0.7725 | 0.8109 | 0.9029 |
| 0.0344 | 9.0 | 4239 | 0.6835 | 0.8705 | 0.7506 | 0.7912 | 0.9010 |
| 0.0276 | 10.0 | 4710 | 0.6916 | 0.8226 | 0.7864 | 0.7999 | 0.9048 |
| 0.0174 | 11.0 | 5181 | 0.7412 | 0.8646 | 0.7491 | 0.7905 | 0.8994 |
| 0.0112 | 12.0 | 5652 | 0.7701 | 0.8258 | 0.7647 | 0.7866 | 0.9018 |
| 0.0084 | 13.0 | 6123 | 0.7811 | 0.8331 | 0.7593 | 0.7899 | 0.9058 |
| 0.0063 | 14.0 | 6594 | 0.7682 | 0.8636 | 0.7763 | 0.8112 | 0.9064 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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