---
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-128
  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-128

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: 0.0131
- Accuracy: 0.9985
- Weighted f1: 0.9985
- Micro f1: 0.9985
- Macro f1: 0.9984
- Weighted recall: 0.9985
- Micro recall: 0.9985
- Macro recall: 0.9984
- Weighted precision: 0.9985
- Micro precision: 0.9985
- Macro precision: 0.9985

## 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: 128
- eval_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 0.2777        | 1.0   | 83   | 0.0230          | 0.9947   | 0.9947      | 0.9947   | 0.9946   | 0.9947          | 0.9947       | 0.9946       | 0.9947             | 0.9947          | 0.9946          |
| 0.0188        | 2.0   | 166  | 0.0131          | 0.9985   | 0.9985      | 0.9985   | 0.9984   | 0.9985          | 0.9985       | 0.9984       | 0.9985             | 0.9985          | 0.9985          |
| 0.0054        | 3.0   | 249  | 0.0084          | 0.9985   | 0.9985      | 0.9985   | 0.9985   | 0.9985          | 0.9985       | 0.9985       | 0.9985             | 0.9985          | 0.9985          |
| 0.0027        | 4.0   | 332  | 0.0077          | 0.9985   | 0.9985      | 0.9985   | 0.9985   | 0.9985          | 0.9985       | 0.9985       | 0.9985             | 0.9985          | 0.9985          |
| 0.0022        | 5.0   | 415  | 0.0084          | 0.9985   | 0.9985      | 0.9985   | 0.9985   | 0.9985          | 0.9985       | 0.9985       | 0.9985             | 0.9985          | 0.9985          |


### Framework versions

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