---
license: apache-2.0
tags:
- generated_from_trainer
base_model: bert-base-multilingual-cased
metrics:
- accuracy
model-index:
- name: fine-tune-berta-TOG-split-headline1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine-tune-berta-TOG-split-headline1

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: 1.1203
- Accuracy: 0.3876

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0797        | 1.0   | 27   | 1.0941          | 0.3828   |
| 1.0888        | 2.0   | 54   | 1.0949          | 0.3828   |
| 1.0863        | 3.0   | 81   | 1.0958          | 0.3828   |
| 1.0757        | 4.0   | 108  | 1.1015          | 0.3923   |
| 1.0443        | 5.0   | 135  | 1.0944          | 0.3732   |
| 1.0329        | 6.0   | 162  | 1.1091          | 0.3732   |
| 0.9922        | 7.0   | 189  | 1.1203          | 0.3876   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1