---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-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. -->

# bert-finetuned-resumes-sections

This model is a fine-tuned version of [dbmdz/bert-base-french-europeana-cased](https://huggingface.co/dbmdz/bert-base-french-europeana-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0272
- F1: 0.9625
- Roc Auc: 0.9793
- Accuracy: 0.9612

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1714        | 1.0   | 554  | 0.0653          | 0.9301 | 0.9515  | 0.9061   |
| 0.0554        | 2.0   | 1108 | 0.0392          | 0.9489 | 0.9679  | 0.9395   |
| 0.033         | 3.0   | 1662 | 0.0318          | 0.9564 | 0.9743  | 0.9512   |
| 0.0212        | 4.0   | 2216 | 0.0295          | 0.9574 | 0.9748  | 0.9530   |
| 0.0155        | 5.0   | 2770 | 0.0282          | 0.9587 | 0.9757  | 0.9548   |
| 0.0138        | 6.0   | 3324 | 0.0282          | 0.9615 | 0.9776  | 0.9584   |
| 0.0108        | 7.0   | 3878 | 0.0272          | 0.9625 | 0.9793  | 0.9612   |
| 0.0081        | 8.0   | 4432 | 0.0284          | 0.9597 | 0.9775  | 0.9584   |
| 0.0077        | 9.0   | 4986 | 0.0267          | 0.9602 | 0.9779  | 0.9584   |
| 0.0058        | 10.0  | 5540 | 0.0281          | 0.9579 | 0.9765  | 0.9566   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1