single_label_unbiased_relevant_profession

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.5581
• Acc At K: 0.8934
• Acc: 0.5742

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Acc At K	Acc
4.1013	0.5	22700	2.6410	0.7356	0.4504
2.3359	1.0	45400	2.1112	0.8115	0.4979
1.9045	1.5	68100	1.9027	0.8428	0.5240
1.7084	2.0	90800	1.7826	0.8607	0.5340
1.5155	2.5	113500	1.7117	0.8711	0.5444
1.4211	3.0	136200	1.6643	0.8782	0.5493
1.2865	3.5	158900	1.6342	0.8812	0.5568
1.2357	4.0	181600	1.6077	0.8852	0.5588
1.1303	4.5	204300	1.6023	0.8873	0.5632
1.0987	5.0	227000	1.5784	0.8896	0.5652
1.0186	5.5	249700	1.5782	0.8904	0.5673
0.9982	6.0	272400	1.5712	0.8914	0.5707
0.9404	6.5	295100	1.5685	0.8920	0.5710
0.9263	7.0	317800	1.5615	0.8925	0.5725
0.8839	7.5	340500	1.5603	0.8929	0.5741
0.878	8.0	363200	1.5581	0.8934	0.5742

Framework versions

• Transformers 4.26.1
• Pytorch 2.0.0+cu117
• Datasets 2.11.0
• Tokenizers 0.13.3