single_label_unbiased_relevant_profession – AI Model by ledigajobb | AlphaNeural AI

You can deploy this model and start earning money today!

ledigajobb/
single_label_unbiased_relevant_profession

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

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