---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-multilingual-cased-language-detection-fp16-false-bs-64
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-multilingual-cased-language-detection-fp16-false-bs-64

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: 0.0103
- Accuracy: 0.9992
- Weighted f1: 0.9992
- Micro f1: 0.9992
- Macro f1: 0.9992
- Weighted recall: 0.9992
- Micro recall: 0.9992
- Macro recall: 0.9992
- Weighted precision: 0.9992
- Micro precision: 0.9992
- Macro precision: 0.9992

## 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: 64
- eval_batch_size: 64
- 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 | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 0.1689        | 1.0   | 165  | 0.0103          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9992          |
| 0.0096        | 2.0   | 330  | 0.0115          | 0.9977   | 0.9977      | 0.9977   | 0.9977   | 0.9977          | 0.9977       | 0.9977       | 0.9977             | 0.9977          | 0.9977          |
| 0.0027        | 3.0   | 495  | 0.0032          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9992          |
| 0.0011        | 4.0   | 660  | 0.0022          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9992          |
| 0.0007        | 5.0   | 825  | 0.0027          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9992          |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4.dev0
- Tokenizers 0.13.3