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---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
base_model: dbmdz/bert-base-french-europeana-cased
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: 0.0333
- F1: 0.9548
- Roc Auc: 0.9732
- Accuracy: 0.9493
## 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: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1659 | 1.0 | 601 | 0.0645 | 0.9201 | 0.9434 | 0.8910 |
| 0.055 | 2.0 | 1202 | 0.0426 | 0.9407 | 0.9633 | 0.9309 |
| 0.0324 | 3.0 | 1803 | 0.0371 | 0.9450 | 0.9663 | 0.9368 |
| 0.0226 | 4.0 | 2404 | 0.0389 | 0.9402 | 0.9651 | 0.9343 |
| 0.0125 | 5.0 | 3005 | 0.0354 | 0.9433 | 0.9650 | 0.9343 |
| 0.0091 | 6.0 | 3606 | 0.0364 | 0.9482 | 0.9696 | 0.9434 |
| 0.0075 | 7.0 | 4207 | 0.0363 | 0.9464 | 0.9676 | 0.9393 |
| 0.007 | 8.0 | 4808 | 0.0333 | 0.9548 | 0.9732 | 0.9493 |
| 0.0063 | 9.0 | 5409 | 0.0358 | 0.9501 | 0.9698 | 0.9434 |
| 0.0043 | 10.0 | 6010 | 0.0380 | 0.9475 | 0.9707 | 0.9443 |
| 0.0032 | 11.0 | 6611 | 0.0377 | 0.9491 | 0.9712 | 0.9468 |
| 0.0031 | 12.0 | 7212 | 0.0375 | 0.9500 | 0.9716 | 0.9459 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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