---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: fine-tuned-distilbert-autofill
  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. -->

# fine-tuned-distilbert-autofill

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0516
- Precision: 0.9887
- Recall: 0.9876
- F1: 0.9878
- Confusion Matrix: [[  93    7    0]
 [  15   43    0]
 [  11    0 2489]]

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Confusion Matrix                                       |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:------------------------------------------------------:|
| No log        | 1.0   | 367  | 0.0597          | 0.9626    | 0.9733 | 0.9659 | [[ 100    0    0]
 [  58    0    0]
 [  13    0 2487]] |
| 0.1186        | 2.0   | 734  | 0.0664          | 0.9622    | 0.9722 | 0.9650 | [[ 100    0    0]
 [  58    0    0]
 [  16    0 2484]] |
| 0.1138        | 3.0   | 1101 | 0.0447          | 0.9873    | 0.9853 | 0.9851 | [[  96    4    0]
 [  25   33    0]
 [   9    1 2490]] |
| 0.1138        | 4.0   | 1468 | 0.0459          | 0.9870    | 0.9857 | 0.9858 | [[  92    8    0]
 [  20   38    0]
 [  10    0 2490]] |
| 0.094         | 5.0   | 1835 | 0.0518          | 0.9872    | 0.9865 | 0.9867 | [[  90   10    0]
 [  16   42    0]
 [   8    2 2490]] |
| 0.0725        | 6.0   | 2202 | 0.0606          | 0.9836    | 0.9808 | 0.9819 | [[  91    9    0]
 [  15   43    0]
 [  11   16 2473]] |
| 0.0811        | 7.0   | 2569 | 0.0572          | 0.9864    | 0.9846 | 0.9849 | [[  93    7    0]
 [  19   39    0]
 [  14    1 2485]] |
| 0.0811        | 8.0   | 2936 | 0.0610          | 0.9861    | 0.9846 | 0.9851 | [[  89   11    0]
 [  15   43    0]
 [  15    0 2485]] |
| 0.0602        | 9.0   | 3303 | 0.0465          | 0.9885    | 0.9868 | 0.9869 | [[  95    5    0]
 [  19   39    0]
 [  11    0 2489]] |
| 0.0457        | 10.0  | 3670 | 0.0516          | 0.9887    | 0.9876 | 0.9878 | [[  93    7    0]
 [  15   43    0]
 [  11    0 2489]] |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1