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README.md
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---
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license: apache-2.0
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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: distilBERT-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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# distilBERT-finetuned-resumes-sections
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.0487
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- F1: 0.9512
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- Roc Auc: 0.9729
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- Accuracy: 0.9482
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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: 20
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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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| 0.058 | 1.0 | 1083 | 0.0457 | 0.9186 | 0.9494 | 0.9020 |
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| 0.0277 | 2.0 | 2166 | 0.0393 | 0.9327 | 0.9614 | 0.9251 |
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| 0.0154 | 3.0 | 3249 | 0.0333 | 0.9425 | 0.9671 | 0.9367 |
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| 0.0104 | 4.0 | 4332 | 0.0408 | 0.9357 | 0.9645 | 0.9293 |
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| 0.0084 | 5.0 | 5415 | 0.0405 | 0.9376 | 0.9643 | 0.9298 |
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| 0.0065 | 6.0 | 6498 | 0.0419 | 0.9439 | 0.9699 | 0.9385 |
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| 0.0051 | 7.0 | 7581 | 0.0450 | 0.9412 | 0.9674 | 0.9376 |
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| 0.0034 | 8.0 | 8664 | 0.0406 | 0.9433 | 0.9684 | 0.9372 |
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| 0.0035 | 9.0 | 9747 | 0.0441 | 0.9403 | 0.9664 | 0.9358 |
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| 0.0024 | 10.0 | 10830 | 0.0492 | 0.9419 | 0.9678 | 0.9367 |
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| 0.0026 | 11.0 | 11913 | 0.0470 | 0.9468 | 0.9708 | 0.9436 |
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| 0.0022 | 12.0 | 12996 | 0.0514 | 0.9424 | 0.9679 | 0.9395 |
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| 0.0013 | 13.0 | 14079 | 0.0458 | 0.9478 | 0.9715 | 0.9441 |
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| 0.0019 | 14.0 | 15162 | 0.0494 | 0.9477 | 0.9711 | 0.9450 |
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| 0.0007 | 15.0 | 16245 | 0.0492 | 0.9496 | 0.9719 | 0.9464 |
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| 0.0009 | 16.0 | 17328 | 0.0487 | 0.9512 | 0.9729 | 0.9482 |
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| 0.001 | 17.0 | 18411 | 0.0510 | 0.9480 | 0.9711 | 0.9441 |
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| 0.0006 | 18.0 | 19494 | 0.0532 | 0.9477 | 0.9709 | 0.9441 |
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| 0.0007 | 19.0 | 20577 | 0.0511 | 0.9487 | 0.9720 | 0.9445 |
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| 0.0005 | 20.0 | 21660 | 0.0522 | 0.9471 | 0.9710 | 0.9436 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.12.0+cu113
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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