---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results_fine_tune_gpt40_original_careful
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# results_fine_tune_gpt40_original_careful

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0019
- Accuracy: 0.9993

## 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: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0049        | 0.8881 | 500  | 0.0082          | 0.9987   |
| 0.0056        | 1.7762 | 1000 | 0.0226          | 0.9973   |
| 0.0062        | 2.6643 | 1500 | 0.0003          | 1.0      |
| 0.0031        | 3.5524 | 2000 | 0.0009          | 0.9993   |
| 0.0006        | 4.4405 | 2500 | 0.0019          | 0.9993   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 2.17.0
- Tokenizers 0.21.0