---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: distilbert-base-multilingual-cased
model-index:
- name: distilbertmultilang
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbertmultilang

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: 1.5628
- Accuracy: 0.7527
- Precision: 0.7353
- Recall: 0.6867
- F1: 0.6967

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 999

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4753        | 1.0   | 761  | 0.5657          | 0.7471   | 0.7146    | 0.6782 | 0.6831 |
| 0.0881        | 2.0   | 1522 | 0.6042          | 0.7728   | 0.7387    | 0.7289 | 0.7329 |
| 0.2734        | 3.0   | 2283 | 0.6275          | 0.7757   | 0.7431    | 0.7504 | 0.7459 |
| 0.0468        | 4.0   | 3044 | 0.9842          | 0.7599   | 0.7362    | 0.7048 | 0.7140 |
| 0.0037        | 5.0   | 3805 | 1.0992          | 0.7715   | 0.7402    | 0.7364 | 0.7374 |
| 0.3644        | 6.0   | 4566 | 1.2696          | 0.7521   | 0.7460    | 0.6853 | 0.6928 |
| 0.0078        | 7.0   | 5327 | 1.3667          | 0.7646   | 0.7329    | 0.7273 | 0.7293 |
| 0.0021        | 8.0   | 6088 | 1.5628          | 0.7527   | 0.7353    | 0.6867 | 0.6967 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2