scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta2

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: 1.0989
• 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: 67
• 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	1.0903	0.3673	0.2479
1.091	2.17	500	1.1006	0.3333	0.1667
1.091	3.26	750	1.0991	0.3333	0.1667
1.0999	4.35	1000	1.0988	0.3333	0.1667
1.0999	5.43	1250	1.0989	0.3333	0.1667
1.0995	6.52	1500	1.0998	0.3333	0.1667
1.0995	7.61	1750	1.0987	0.3333	0.1667
1.0993	8.7	2000	1.0987	0.3333	0.1667
1.0993	9.78	2250	1.0987	0.3333	0.1667
1.1002	10.87	2500	1.0987	0.3333	0.1667
1.1002	11.96	2750	1.0988	0.3333	0.1667
1.0996	13.04	3000	1.0987	0.3333	0.1667
1.0996	14.13	3250	1.0990	0.3333	0.1667
1.0991	15.22	3500	1.0987	0.3333	0.1667
1.0991	16.3	3750	1.0987	0.3333	0.1667
1.0992	17.39	4000	1.0986	0.3333	0.1667
1.0992	18.48	4250	1.0987	0.3333	0.1667
1.0991	19.57	4500	1.0987	0.3333	0.1667
1.0991	20.65	4750	1.0987	0.3333	0.1667
1.099	21.74	5000	1.0988	0.3333	0.1667
1.099	22.83	5250	1.0987	0.3333	0.1667
1.099	23.91	5500	1.0987	0.3333	0.1667
1.099	25.0	5750	1.0986	0.3333	0.1667
1.0988	26.09	6000	1.0991	0.3333	0.1667
1.0988	27.17	6250	1.0991	0.3333	0.1667
1.0988	28.26	6500	1.0990	0.3333	0.1667
1.0988	29.35	6750	1.0989	0.3333	0.1667

Framework versions

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