20230928-4-xlm-roberta-base-new

This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

• Accuracy: 0.4562
• Loss: nan

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: 10

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
4.6239	0.46	200	0.3344	nan
4.1206	0.91	400	0.3185	nan
3.7736	1.37	600	0.3455	nan
3.7553	1.82	800	0.3323	nan
3.4994	2.28	1000	0.4056	nan
3.4706	2.73	1200	0.4070	nan
3.3323	3.19	1400	0.4458	3.0068
3.2846	3.64	1600	0.4343	nan
3.3462	4.1	1800	0.4954	2.5325
3.0349	4.56	2000	0.4235	2.9762
3.1044	5.01	2200	0.3799	nan
2.9192	5.47	2400	0.5046	2.6744
3.0091	5.92	2600	0.4533	2.8950
2.8518	6.38	2800	0.4604	nan
2.867	6.83	3000	0.4475	2.5855
2.9242	7.29	3200	0.4737	2.7730
2.7668	7.74	3400	0.4661	nan
2.7914	8.2	3600	0.4735	2.8640
2.945	8.66	3800	0.5014	2.8195
2.7329	9.11	4000	0.4758	nan
2.8379	9.57	4200	0.4562	nan

Framework versions

• Transformers 4.33.3
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3