scenario-TCR-XLMV_data-en-cardiff_eng_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: 1.0986
• 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: 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	1.03	60	1.0981	0.3677	0.3195
No log	2.07	120	1.0990	0.3333	0.1667
No log	3.1	180	1.0989	0.3333	0.1667
No log	4.14	240	1.0987	0.3333	0.1667
No log	5.17	300	1.0986	0.3333	0.1667
No log	6.21	360	1.0989	0.3333	0.1667
No log	7.24	420	1.0992	0.3333	0.1667
No log	8.28	480	1.0986	0.3333	0.1667
1.1002	9.31	540	1.0994	0.3333	0.1667
1.1002	10.34	600	1.0987	0.3333	0.1667
1.1002	11.38	660	1.0986	0.3333	0.1667
1.1002	12.41	720	1.0987	0.3333	0.1667
1.1002	13.45	780	1.0987	0.3333	0.1667
1.1002	14.48	840	1.0987	0.3333	0.1667
1.1002	15.52	900	1.0991	0.3333	0.1667
1.1002	16.55	960	1.0988	0.3333	0.1667
1.1	17.59	1020	1.0987	0.3333	0.1667
1.1	18.62	1080	1.0987	0.3333	0.1667
1.1	19.66	1140	1.0988	0.3333	0.1667
1.1	20.69	1200	1.0987	0.3333	0.1667
1.1	21.72	1260	1.0987	0.3333	0.1667
1.1	22.76	1320	1.0986	0.3333	0.1667
1.1	23.79	1380	1.0987	0.3333	0.1667
1.1	24.83	1440	1.0986	0.3333	0.1667
1.0989	25.86	1500	1.0986	0.3333	0.1667
1.0989	26.9	1560	1.0986	0.3333	0.1667
1.0989	27.93	1620	1.0986	0.3333	0.1667
1.0989	28.97	1680	1.0986	0.3333	0.1667
1.0989	30.0	1740	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