xlm-roberta-base-sun-MICRO

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

• Loss: 0.2865
• F1: 0.7748
• Roc Auc: 0.8504
• Accuracy: 0.6122

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 100
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.3514	1.0	103	0.3448	0.6745	0.7760	0.5707
0.3815	2.0	206	0.3401	0.6745	0.7760	0.5707
0.3462	3.0	309	0.3261	0.6745	0.7760	0.5707
0.2737	4.0	412	0.2872	0.7345	0.8100	0.6293
0.2769	5.0	515	0.2814	0.7457	0.8167	0.6390
0.2756	6.0	618	0.2670	0.7297	0.8008	0.6049
0.2228	7.0	721	0.2704	0.7489	0.8193	0.6244
0.2371	8.0	824	0.2540	0.7570	0.8204	0.6390
0.2084	9.0	927	0.2684	0.7613	0.8415	0.5902
0.1813	10.0	1030	0.2678	0.7678	0.8415	0.6268
0.1993	11.0	1133	0.2720	0.7654	0.8396	0.6122
0.1738	12.0	1236	0.2725	0.7698	0.8427	0.6122
0.1558	13.0	1339	0.2886	0.7626	0.8381	0.6122
0.1579	14.0	1442	0.2784	0.7624	0.8413	0.6
0.1581	15.0	1545	0.2874	0.7700	0.8493	0.6024
0.1276	16.0	1648	0.2868	0.7697	0.8470	0.6024
0.1325	17.0	1751	0.2865	0.7748	0.8504	0.6122
0.1254	18.0	1854	0.2881	0.7671	0.8440	0.6049
0.1453	19.0	1957	0.2882	0.7695	0.8459	0.6073
0.1161	20.0	2060	0.2881	0.7663	0.8437	0.6024

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0