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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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model-index:
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- name: bert-finetuned-resumes-sections
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bert-finetuned-resumes-sections
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.0272
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- F1: 0.9625
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- Roc Auc: 0.9793
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- Accuracy: 0.9612
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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| 0.1714 | 1.0 | 554 | 0.0653 | 0.9301 | 0.9515 | 0.9061 |
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| 0.0554 | 2.0 | 1108 | 0.0392 | 0.9489 | 0.9679 | 0.9395 |
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| 0.033 | 3.0 | 1662 | 0.0318 | 0.9564 | 0.9743 | 0.9512 |
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| 0.0212 | 4.0 | 2216 | 0.0295 | 0.9574 | 0.9748 | 0.9530 |
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| 0.0155 | 5.0 | 2770 | 0.0282 | 0.9587 | 0.9757 | 0.9548 |
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| 0.0138 | 6.0 | 3324 | 0.0282 | 0.9615 | 0.9776 | 0.9584 |
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| 0.0108 | 7.0 | 3878 | 0.0272 | 0.9625 | 0.9793 | 0.9612 |
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| 0.0081 | 8.0 | 4432 | 0.0284 | 0.9597 | 0.9775 | 0.9584 |
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| 0.0077 | 9.0 | 4986 | 0.0267 | 0.9602 | 0.9779 | 0.9584 |
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| 0.0058 | 10.0 | 5540 | 0.0281 | 0.9579 | 0.9765 | 0.9566 |
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### Framework versions
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- Transformers 4.19.2
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- Pytorch 1.11.0+cu113
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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