---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: output
  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. -->

# output

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: 0.9285
- Accuracy: 0.51

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4791        | 1.0   | 94   | 0.8476          | 0.5587   |
| 0.654         | 2.0   | 188  | 0.7250          | 0.564    |
| 0.6278        | 3.0   | 282  | 0.7372          | 0.5393   |
| 0.5884        | 4.0   | 376  | 0.8102          | 0.5503   |
| 0.5493        | 5.0   | 470  | 0.8603          | 0.5183   |
| 0.5265        | 6.0   | 564  | 0.9099          | 0.5213   |
| 0.4908        | 7.0   | 658  | 0.9285          | 0.51     |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1