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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: 0.0333 |
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- F1: 0.9548 |
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- Roc Auc: 0.9732 |
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- Accuracy: 0.9493 |
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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: 12 |
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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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| 0.1659 | 1.0 | 601 | 0.0645 | 0.9201 | 0.9434 | 0.8910 | |
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| 0.055 | 2.0 | 1202 | 0.0426 | 0.9407 | 0.9633 | 0.9309 | |
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| 0.0324 | 3.0 | 1803 | 0.0371 | 0.9450 | 0.9663 | 0.9368 | |
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| 0.0226 | 4.0 | 2404 | 0.0389 | 0.9402 | 0.9651 | 0.9343 | |
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| 0.0125 | 5.0 | 3005 | 0.0354 | 0.9433 | 0.9650 | 0.9343 | |
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| 0.0091 | 6.0 | 3606 | 0.0364 | 0.9482 | 0.9696 | 0.9434 | |
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| 0.0075 | 7.0 | 4207 | 0.0363 | 0.9464 | 0.9676 | 0.9393 | |
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| 0.007 | 8.0 | 4808 | 0.0333 | 0.9548 | 0.9732 | 0.9493 | |
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| 0.0063 | 9.0 | 5409 | 0.0358 | 0.9501 | 0.9698 | 0.9434 | |
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| 0.0043 | 10.0 | 6010 | 0.0380 | 0.9475 | 0.9707 | 0.9443 | |
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| 0.0032 | 11.0 | 6611 | 0.0377 | 0.9491 | 0.9712 | 0.9468 | |
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| 0.0031 | 12.0 | 7212 | 0.0375 | 0.9500 | 0.9716 | 0.9459 | |
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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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