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---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: result-colab
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. -->
# result-colab
This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3751
- Accuracy: 0.8853
- Precision: 0.8785
- Recall: 0.8773
- F1: 0.8773
## 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: 1e-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: cosine
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.3635 | 1.0 | 48 | 1.1593 | 0.5963 | 0.4671 | 0.5259 | 0.4501 |
| 0.9895 | 2.0 | 96 | 0.7987 | 0.6881 | 0.6824 | 0.6271 | 0.6017 |
| 0.6845 | 3.0 | 144 | 0.6432 | 0.7523 | 0.7789 | 0.7076 | 0.7071 |
| 0.5856 | 4.0 | 192 | 0.5896 | 0.7844 | 0.8315 | 0.7457 | 0.7463 |
| 0.4328 | 5.0 | 240 | 0.4232 | 0.8716 | 0.8750 | 0.8585 | 0.8645 |
| 0.4298 | 6.0 | 288 | 0.4118 | 0.8853 | 0.8783 | 0.8810 | 0.8789 |
| 0.322 | 7.0 | 336 | 0.3988 | 0.8807 | 0.8824 | 0.8655 | 0.8712 |
| 0.3561 | 8.0 | 384 | 0.4169 | 0.8716 | 0.8630 | 0.8679 | 0.8637 |
| 0.27 | 9.0 | 432 | 0.3779 | 0.8991 | 0.8972 | 0.8913 | 0.8938 |
| 0.2472 | 10.0 | 480 | 0.3850 | 0.8991 | 0.8928 | 0.8942 | 0.8924 |
| 0.2349 | 11.0 | 528 | 0.3749 | 0.8945 | 0.8855 | 0.8919 | 0.8875 |
| 0.2491 | 12.0 | 576 | 0.3798 | 0.9037 | 0.8969 | 0.8992 | 0.8975 |
| 0.2239 | 13.0 | 624 | 0.3778 | 0.8853 | 0.8783 | 0.8810 | 0.8793 |
| 0.2276 | 14.0 | 672 | 0.3755 | 0.8899 | 0.8827 | 0.8823 | 0.8822 |
| 0.206 | 15.0 | 720 | 0.3751 | 0.8853 | 0.8785 | 0.8773 | 0.8773 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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