scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta

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

• Loss: 1.0986
• Accuracy: 0.3333
• F1: 0.1667

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 112233
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.09	250	1.0993	0.3333	0.1667
1.1009	2.17	500	1.0989	0.3333	0.1667
1.1009	3.26	750	1.0998	0.3333	0.1667
1.0998	4.35	1000	1.0991	0.3333	0.1667
1.0998	5.43	1250	1.0987	0.3333	0.1667
1.1003	6.52	1500	1.0991	0.3333	0.1667
1.1003	7.61	1750	1.0999	0.3333	0.1667
1.1001	8.7	2000	1.0988	0.3333	0.1667
1.1001	9.78	2250	1.0986	0.3333	0.1667
1.0996	10.87	2500	1.0989	0.3333	0.1667
1.0996	11.96	2750	1.0989	0.3333	0.1667
1.1001	13.04	3000	1.0986	0.3333	0.1667
1.1001	14.13	3250	1.0994	0.3333	0.1667
1.0981	15.22	3500	1.1405	0.3333	0.1667
1.0981	16.3	3750	1.0987	0.3333	0.1667
1.0993	17.39	4000	1.0987	0.3333	0.1667
1.0993	18.48	4250	1.0990	0.3333	0.1667
1.0987	19.57	4500	1.0978	0.3457	0.2853
1.0987	20.65	4750	1.0999	0.3380	0.2148
1.0943	21.74	5000	1.0987	0.3333	0.1667
1.0943	22.83	5250	1.0987	0.3333	0.1667
1.0991	23.91	5500	1.0986	0.3333	0.1667
1.0991	25.0	5750	1.0986	0.3333	0.1667
1.0988	26.09	6000	1.0986	0.3333	0.1667
1.0988	27.17	6250	1.0986	0.3333	0.1667
1.0991	28.26	6500	1.0986	0.3333	0.1667
1.0991	29.35	6750	1.0986	0.3333	0.1667

Framework versions

• Transformers 4.33.3
• Pytorch 2.1.1+cu121
• Datasets 2.14.5
• Tokenizers 0.13.3