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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: 0.0450 |
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- F1: 0.9585 |
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- Roc Auc: 0.9774 |
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- Accuracy: 0.9557 |
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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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| 0.0518 | 1.0 | 1174 | 0.0368 | 0.9406 | 0.9635 | 0.9302 | |
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| 0.0251 | 2.0 | 2348 | 0.0346 | 0.9375 | 0.9653 | 0.9289 | |
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| 0.0136 | 3.0 | 3522 | 0.0343 | 0.9475 | 0.9707 | 0.9425 | |
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| 0.0096 | 4.0 | 4696 | 0.0326 | 0.9539 | 0.9737 | 0.9468 | |
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| 0.007 | 5.0 | 5870 | 0.0357 | 0.9521 | 0.9740 | 0.9480 | |
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| 0.007 | 6.0 | 7044 | 0.0389 | 0.9509 | 0.9725 | 0.9472 | |
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| 0.0034 | 7.0 | 8218 | 0.0403 | 0.9532 | 0.9746 | 0.9510 | |
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| 0.0033 | 8.0 | 9392 | 0.0422 | 0.9493 | 0.9722 | 0.9468 | |
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| 0.0024 | 9.0 | 10566 | 0.0425 | 0.9512 | 0.9733 | 0.9485 | |
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| 0.0023 | 10.0 | 11740 | 0.0431 | 0.9537 | 0.9743 | 0.9502 | |
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| 0.0019 | 11.0 | 12914 | 0.0457 | 0.9501 | 0.9719 | 0.9463 | |
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| 0.002 | 12.0 | 14088 | 0.0428 | 0.9560 | 0.9751 | 0.9536 | |
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| 0.0012 | 13.0 | 15262 | 0.0435 | 0.9569 | 0.9761 | 0.9553 | |
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| 0.001 | 14.0 | 16436 | 0.0464 | 0.9565 | 0.9759 | 0.9544 | |
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| 0.001 | 15.0 | 17610 | 0.0460 | 0.9574 | 0.9766 | 0.9549 | |
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| 0.0007 | 16.0 | 18784 | 0.0450 | 0.9585 | 0.9774 | 0.9557 | |
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| 0.0003 | 17.0 | 19958 | 0.0481 | 0.9572 | 0.9764 | 0.9553 | |
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| 0.0005 | 18.0 | 21132 | 0.0478 | 0.9576 | 0.9764 | 0.9557 | |
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| 0.0005 | 19.0 | 22306 | 0.0483 | 0.9574 | 0.9766 | 0.9553 | |
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| 0.0005 | 20.0 | 23480 | 0.0481 | 0.9576 | 0.9766 | 0.9557 | |
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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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