---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: distilBERT-finetuned-resumes-sections
  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-finetuned-resumes-sections

This model is a fine-tuned version of [Geotrend/distilbert-base-en-fr-cased](https://huggingface.co/Geotrend/distilbert-base-en-fr-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0450
- F1: 0.9585
- Roc Auc: 0.9774
- Accuracy: 0.9557

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.0518        | 1.0   | 1174  | 0.0368          | 0.9406 | 0.9635  | 0.9302   |
| 0.0251        | 2.0   | 2348  | 0.0346          | 0.9375 | 0.9653  | 0.9289   |
| 0.0136        | 3.0   | 3522  | 0.0343          | 0.9475 | 0.9707  | 0.9425   |
| 0.0096        | 4.0   | 4696  | 0.0326          | 0.9539 | 0.9737  | 0.9468   |
| 0.007         | 5.0   | 5870  | 0.0357          | 0.9521 | 0.9740  | 0.9480   |
| 0.007         | 6.0   | 7044  | 0.0389          | 0.9509 | 0.9725  | 0.9472   |
| 0.0034        | 7.0   | 8218  | 0.0403          | 0.9532 | 0.9746  | 0.9510   |
| 0.0033        | 8.0   | 9392  | 0.0422          | 0.9493 | 0.9722  | 0.9468   |
| 0.0024        | 9.0   | 10566 | 0.0425          | 0.9512 | 0.9733  | 0.9485   |
| 0.0023        | 10.0  | 11740 | 0.0431          | 0.9537 | 0.9743  | 0.9502   |
| 0.0019        | 11.0  | 12914 | 0.0457          | 0.9501 | 0.9719  | 0.9463   |
| 0.002         | 12.0  | 14088 | 0.0428          | 0.9560 | 0.9751  | 0.9536   |
| 0.0012        | 13.0  | 15262 | 0.0435          | 0.9569 | 0.9761  | 0.9553   |
| 0.001         | 14.0  | 16436 | 0.0464          | 0.9565 | 0.9759  | 0.9544   |
| 0.001         | 15.0  | 17610 | 0.0460          | 0.9574 | 0.9766  | 0.9549   |
| 0.0007        | 16.0  | 18784 | 0.0450          | 0.9585 | 0.9774  | 0.9557   |
| 0.0003        | 17.0  | 19958 | 0.0481          | 0.9572 | 0.9764  | 0.9553   |
| 0.0005        | 18.0  | 21132 | 0.0478          | 0.9576 | 0.9764  | 0.9557   |
| 0.0005        | 19.0  | 22306 | 0.0483          | 0.9574 | 0.9766  | 0.9553   |
| 0.0005        | 20.0  | 23480 | 0.0481          | 0.9576 | 0.9766  | 0.9557   |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1