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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: extended_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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# extended_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: 0.0321 |
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- F1: 0.9735 |
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- Roc Auc: 0.9850 |
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- Accuracy: 0.9715 |
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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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| 0.0283 | 1.0 | 2213 | 0.0247 | 0.9610 | 0.9763 | 0.9539 | |
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| 0.0153 | 2.0 | 4426 | 0.0223 | 0.9634 | 0.9789 | 0.9593 | |
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| 0.01 | 3.0 | 6639 | 0.0199 | 0.9702 | 0.9835 | 0.9675 | |
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| 0.0073 | 4.0 | 8852 | 0.0218 | 0.9710 | 0.9838 | 0.9690 | |
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| 0.0063 | 5.0 | 11065 | 0.0244 | 0.9706 | 0.9835 | 0.9684 | |
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| 0.0037 | 6.0 | 13278 | 0.0251 | 0.9700 | 0.9833 | 0.9684 | |
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| 0.004 | 7.0 | 15491 | 0.0273 | 0.9712 | 0.9837 | 0.9693 | |
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| 0.003 | 8.0 | 17704 | 0.0266 | 0.9719 | 0.9841 | 0.9695 | |
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| 0.0027 | 9.0 | 19917 | 0.0294 | 0.9697 | 0.9831 | 0.9679 | |
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| 0.0014 | 10.0 | 22130 | 0.0275 | 0.9714 | 0.9844 | 0.9690 | |
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| 0.0016 | 11.0 | 24343 | 0.0299 | 0.9714 | 0.9839 | 0.9697 | |
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| 0.0013 | 12.0 | 26556 | 0.0297 | 0.9719 | 0.9852 | 0.9697 | |
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| 0.0006 | 13.0 | 28769 | 0.0312 | 0.9711 | 0.9843 | 0.9697 | |
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| 0.0004 | 14.0 | 30982 | 0.0305 | 0.9731 | 0.9849 | 0.9720 | |
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| 0.0004 | 15.0 | 33195 | 0.0312 | 0.9723 | 0.9845 | 0.9704 | |
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| 0.0005 | 16.0 | 35408 | 0.0331 | 0.9716 | 0.9843 | 0.9697 | |
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| 0.0006 | 17.0 | 37621 | 0.0321 | 0.9735 | 0.9850 | 0.9715 | |
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| 0.0004 | 18.0 | 39834 | 0.0322 | 0.9731 | 0.9850 | 0.9711 | |
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| 0.0003 | 19.0 | 42047 | 0.0332 | 0.9722 | 0.9847 | 0.9706 | |
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| 0.0004 | 20.0 | 44260 | 0.0334 | 0.9720 | 0.9846 | 0.9704 | |
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### Framework versions |
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- Transformers 4.21.3 |
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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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