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

# distilbert-lang-detect

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1215
- Accuracy: 0.9720
- F1: 0.9720
- Precision: 0.9720
- Recall: 0.9720

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- 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 | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1022        | 1.0   | 14547 | 0.0924          | 0.9703   | 0.9703 | 0.9703    | 0.9703 |
| 0.0783        | 2.0   | 29094 | 0.0924          | 0.9704   | 0.9704 | 0.9705    | 0.9704 |
| 0.0646        | 3.0   | 43641 | 0.1096          | 0.9724   | 0.9724 | 0.9725    | 0.9724 |
| 0.053         | 4.0   | 58188 | 0.1188          | 0.9722   | 0.9722 | 0.9722    | 0.9722 |
| 0.0364        | 5.0   | 72735 | 0.1215          | 0.9720   | 0.9720 | 0.9720    | 0.9720 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0