---
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-true
  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-base-multilingual-cased-language-detection-fp16-true

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: 0.0006
- Accuracy: 1.0
- Weighted f1: 1.0
- Micro f1: 1.0
- Macro f1: 1.0
- Weighted recall: 1.0
- Micro recall: 1.0
- Macro recall: 1.0
- Weighted precision: 1.0
- Micro precision: 1.0
- Macro precision: 1.0

## 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: 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 | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 0.0814        | 1.0   | 658  | 0.0041          | 0.9985   | 0.9985      | 0.9985   | 0.9985   | 0.9985          | 0.9985       | 0.9985       | 0.9985             | 0.9985          | 0.9985          |
| 0.0063        | 2.0   | 1316 | 0.0011          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9993       | 0.9992             | 0.9992          | 0.9992          |
| 0.0008        | 3.0   | 1974 | 0.0006          | 1.0      | 1.0         | 1.0      | 1.0      | 1.0             | 1.0          | 1.0          | 1.0                | 1.0             | 1.0             |
| 0.0001        | 4.0   | 2632 | 0.0013          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9993       | 0.9992             | 0.9992          | 0.9992          |
| 0.0001        | 5.0   | 3290 | 0.0013          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9993       | 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