---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_B08
  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_B08

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: 0.3054
- Precision: 0.6335
- Recall: 0.6849
- F1: 0.6582
- Accuracy: 0.9094

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3792        | 1.0   | 92   | 0.3446          | 0.6004    | 0.5913 | 0.5958 | 0.8982   |
| 0.2782        | 2.0   | 184  | 0.2911          | 0.6485    | 0.6664 | 0.6573 | 0.9110   |
| 0.1736        | 3.0   | 276  | 0.2886          | 0.6570    | 0.6730 | 0.6649 | 0.9123   |
| 0.1434        | 4.0   | 368  | 0.2974          | 0.6481    | 0.6763 | 0.6619 | 0.9109   |
| 0.1422        | 5.0   | 460  | 0.3054          | 0.6335    | 0.6849 | 0.6582 | 0.9094   |


### Framework versions

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