extended_distilBERT-finetuned-resumes-sections

This model is a fine-tuned version of Geotrend/distilbert-base-en-fr-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0321
• F1: 0.9735
• Roc Auc: 0.9850
• Accuracy: 0.9715

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

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

Framework versions

• Transformers 4.21.3
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1