scenario-TCR-XLMV_data-cl-cardiff_cl_only_gamma

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: 11423
• 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	1.1044	0.3333	0.1667
1.0991	2.17	500	1.0996	0.3333	0.1667
1.0991	3.26	750	1.0992	0.3333	0.1667
1.1001	4.35	1000	1.0986	0.3333	0.1667
1.1001	5.43	1250	1.0998	0.3333	0.1667
1.0995	6.52	1500	1.0986	0.3333	0.1667
1.0995	7.61	1750	1.0987	0.3333	0.1667
1.0994	8.7	2000	1.0993	0.3333	0.1667
1.0994	9.78	2250	1.0996	0.3333	0.1667
1.0997	10.87	2500	1.0987	0.3333	0.1667
1.0997	11.96	2750	1.0989	0.3333	0.1667
1.0992	13.04	3000	1.0987	0.3333	0.1667
1.0992	14.13	3250	1.0987	0.3333	0.1667
1.0994	15.22	3500	1.0988	0.3333	0.1667
1.0994	16.3	3750	1.0987	0.3333	0.1667
1.0991	17.39	4000	1.0988	0.3333	0.1667
1.0991	18.48	4250	1.0986	0.3333	0.1667
1.0992	19.57	4500	1.0986	0.3333	0.1667
1.0992	20.65	4750	1.0986	0.3333	0.1667
1.099	21.74	5000	1.0987	0.3333	0.1667
1.099	22.83	5250	1.0986	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	1.0987	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