---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4465
- Accuracy: 0.8226
- F1: 0.8220
- Precision: 0.8231
- Recall: 0.8226

## 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: 4.993596574084884e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0218        | 1.0   | 622  | 0.8816          | 0.5732   | 0.5732 | 0.5812    | 0.5732 |
| 0.8654        | 2.0   | 1244 | 0.7610          | 0.6600   | 0.6539 | 0.6620    | 0.6600 |
| 0.7534        | 3.0   | 1866 | 0.6904          | 0.6962   | 0.6912 | 0.7079    | 0.6962 |
| 0.6593        | 4.0   | 2488 | 0.6406          | 0.7342   | 0.7290 | 0.7454    | 0.7342 |
| 0.5278        | 5.0   | 3110 | 0.5557          | 0.7740   | 0.7732 | 0.7763    | 0.7740 |
| 0.4939        | 6.0   | 3732 | 0.5420          | 0.7776   | 0.7764 | 0.7819    | 0.7776 |
| 0.4585        | 7.0   | 4354 | 0.5258          | 0.7920   | 0.7899 | 0.7999    | 0.7920 |
| 0.4181        | 8.0   | 4976 | 0.5013          | 0.8029   | 0.8023 | 0.8046    | 0.8029 |
| 0.3804        | 9.0   | 5598 | 0.4922          | 0.8065   | 0.8053 | 0.8109    | 0.8065 |
| 0.3642        | 10.0  | 6220 | 0.4823          | 0.8065   | 0.8056 | 0.8085    | 0.8065 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1