---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_B09
  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. -->

# BERT_B09

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: 0.2572
- Precision: 0.6376
- Recall: 0.6753
- F1: 0.6559
- Accuracy: 0.9287

## 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- label_smoothing_factor: 0.001

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4255        | 1.0   | 46   | 0.3653          | 0.4807    | 0.5043 | 0.4922 | 0.9019   |
| 0.2621        | 2.0   | 92   | 0.2719          | 0.6056    | 0.6101 | 0.6078 | 0.9227   |
| 0.1642        | 3.0   | 138  | 0.2659          | 0.6047    | 0.6605 | 0.6314 | 0.9246   |
| 0.1249        | 4.0   | 184  | 0.2580          | 0.6382    | 0.6617 | 0.6498 | 0.9299   |
| 0.1232        | 5.0   | 230  | 0.2572          | 0.6376    | 0.6753 | 0.6559 | 0.9287   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3