scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta2

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: 2
• 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	1.0987	0.3341	0.1684
1.0996	2.17	500	1.0994	0.3333	0.1667
1.0996	3.26	750	1.0988	0.3333	0.1667
1.0998	4.35	1000	1.0987	0.3333	0.1667
1.0998	5.43	1250	1.1001	0.3333	0.1667
1.1001	6.52	1500	1.0986	0.3333	0.1667
1.1001	7.61	1750	1.0988	0.3333	0.1667
1.0994	8.7	2000	1.0988	0.3333	0.1667
1.0994	9.78	2250	1.1048	0.3333	0.1667
1.0998	10.87	2500	1.0988	0.3333	0.1667
1.0998	11.96	2750	1.0987	0.3333	0.1667
1.1001	13.04	3000	1.0986	0.3333	0.1667
1.1001	14.13	3250	1.0989	0.3333	0.1667
1.0994	15.22	3500	1.0991	0.3333	0.1667
1.0994	16.3	3750	1.0987	0.3333	0.1667
1.0989	17.39	4000	1.0989	0.3333	0.1667
1.0989	18.48	4250	1.0988	0.3333	0.1667
1.0991	19.57	4500	1.0988	0.3333	0.1667
1.0991	20.65	4750	1.0988	0.3333	0.1667
1.0992	21.74	5000	1.0988	0.3333	0.1667
1.0992	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	1.0987	0.3333	0.1667
1.0989	26.09	6000	1.0986	0.3333	0.1667
1.0989	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