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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-with_tokenizer
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-with_tokenizer
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: 0.3390
- Accuracy: 0.8945
- Precision: 0.8847
- Recall: 0.8927
- F1: 0.8869
## 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: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2288 | 1.0 | 48 | 0.9276 | 0.6789 | 0.5929 | 0.6138 | 0.5825 |
| 0.7686 | 2.0 | 96 | 0.5879 | 0.7661 | 0.7354 | 0.7159 | 0.7019 |
| 0.5665 | 3.0 | 144 | 0.4706 | 0.8440 | 0.8498 | 0.8238 | 0.8281 |
| 0.4813 | 4.0 | 192 | 0.4045 | 0.8578 | 0.8514 | 0.8329 | 0.8354 |
| 0.3716 | 5.0 | 240 | 0.3770 | 0.8624 | 0.8566 | 0.8398 | 0.8426 |
| 0.3535 | 6.0 | 288 | 0.3538 | 0.8853 | 0.8760 | 0.8664 | 0.8690 |
| 0.2511 | 7.0 | 336 | 0.3626 | 0.8716 | 0.8631 | 0.8573 | 0.8591 |
| 0.2826 | 8.0 | 384 | 0.3490 | 0.8899 | 0.8809 | 0.8886 | 0.8823 |
| 0.2295 | 9.0 | 432 | 0.3372 | 0.8807 | 0.8697 | 0.8720 | 0.8705 |
| 0.181 | 10.0 | 480 | 0.3410 | 0.8853 | 0.8743 | 0.8789 | 0.8757 |
| 0.178 | 11.0 | 528 | 0.3416 | 0.8945 | 0.8847 | 0.8927 | 0.8869 |
| 0.208 | 12.0 | 576 | 0.3390 | 0.8945 | 0.8847 | 0.8927 | 0.8869 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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