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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: 0.0369 |
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- F1: 0.9652 |
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- Roc Auc: 0.9808 |
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- Accuracy: 0.9621 |
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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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| 0.0509 | 1.0 | 1173 | 0.0331 | 0.9439 | 0.9659 | 0.9356 | |
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| 0.024 | 2.0 | 2346 | 0.0274 | 0.9550 | 0.9750 | 0.9493 | |
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| 0.0148 | 3.0 | 3519 | 0.0290 | 0.9493 | 0.9712 | 0.9446 | |
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| 0.0089 | 4.0 | 4692 | 0.0324 | 0.9492 | 0.9714 | 0.9442 | |
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| 0.0071 | 5.0 | 5865 | 0.0317 | 0.9540 | 0.9732 | 0.9476 | |
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| 0.0064 | 6.0 | 7038 | 0.0324 | 0.9527 | 0.9742 | 0.9484 | |
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| 0.0036 | 7.0 | 8211 | 0.0320 | 0.9574 | 0.9766 | 0.9540 | |
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| 0.0042 | 8.0 | 9384 | 0.0367 | 0.9528 | 0.9732 | 0.9493 | |
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| 0.0052 | 9.0 | 10557 | 0.0342 | 0.9563 | 0.9757 | 0.9531 | |
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| 0.0027 | 10.0 | 11730 | 0.0294 | 0.9629 | 0.9800 | 0.9595 | |
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| 0.0017 | 11.0 | 12903 | 0.0355 | 0.9605 | 0.9778 | 0.9582 | |
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| 0.0022 | 12.0 | 14076 | 0.0338 | 0.9627 | 0.9792 | 0.9591 | |
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| 0.0012 | 13.0 | 15249 | 0.0358 | 0.9609 | 0.9780 | 0.9591 | |
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| 0.0011 | 14.0 | 16422 | 0.0360 | 0.9618 | 0.9791 | 0.9604 | |
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| 0.0009 | 15.0 | 17595 | 0.0358 | 0.9648 | 0.9807 | 0.9625 | |
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| 0.0007 | 16.0 | 18768 | 0.0373 | 0.9627 | 0.9794 | 0.9595 | |
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| 0.0006 | 17.0 | 19941 | 0.0397 | 0.9597 | 0.9774 | 0.9574 | |
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| 0.0008 | 18.0 | 21114 | 0.0369 | 0.9652 | 0.9808 | 0.9621 | |
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| 0.0007 | 19.0 | 22287 | 0.0377 | 0.9646 | 0.9801 | 0.9621 | |
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| 0.0005 | 20.0 | 23460 | 0.0381 | 0.9639 | 0.9797 | 0.9616 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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