scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta

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: 1.0448
• Accuracy: 0.4838
• F1: 0.4798

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: 11213
• 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	1.0988	0.3333	0.1667
1.0959	2.17	500	1.0989	0.3333	0.1667
1.0959	3.26	750	1.1000	0.3333	0.1667
1.0996	4.35	1000	1.1023	0.3333	0.1667
1.0996	5.43	1250	1.0990	0.3333	0.1667
1.1001	6.52	1500	1.0997	0.3333	0.1667
1.1001	7.61	1750	1.0998	0.3333	0.1667
1.0992	8.7	2000	1.0988	0.3333	0.1667
1.0992	9.78	2250	1.0990	0.3333	0.1667
1.0998	10.87	2500	1.0992	0.3333	0.1667
1.0998	11.96	2750	1.0996	0.3333	0.1667
1.0994	13.04	3000	1.0987	0.3333	0.1667
1.0994	14.13	3250	1.0988	0.3333	0.1667
1.0993	15.22	3500	1.0993	0.3333	0.1667
1.0993	16.3	3750	1.0987	0.3333	0.1667
1.0995	17.39	4000	1.0986	0.3333	0.1667
1.0995	18.48	4250	1.0989	0.3333	0.1667
1.0991	19.57	4500	1.0989	0.3333	0.1667
1.0991	20.65	4750	1.0987	0.3333	0.1667
1.0994	21.74	5000	1.0987	0.3333	0.1667
1.0994	22.83	5250	1.0987	0.3333	0.1667
1.0991	23.91	5500	1.0987	0.3333	0.1667
1.0991	25.0	5750	1.0986	0.3333	0.1667
1.0991	26.09	6000	1.0987	0.3333	0.1667
1.0991	27.17	6250	1.0986	0.3333	0.1667
1.0946	28.26	6500	1.0796	0.4560	0.4220
1.0946	29.35	6750	1.0448	0.4838	0.4798

Framework versions

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