scenario-KD-SCR-CDF-CL-D2_data-cl-cardiff_cl_only66

This model is a fine-tuned version of haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only on the None dataset. It achieves the following results on the evaluation set:

• Loss: nan
• 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: 66
• 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	nan	0.3333	0.1667
1.0392	2.17	500	nan	0.3333	0.1667
1.0392	3.26	750	nan	0.3333	0.1667
0.0	4.35	1000	nan	0.3333	0.1667
0.0	5.43	1250	nan	0.3333	0.1667
0.0	6.52	1500	nan	0.3333	0.1667
0.0	7.61	1750	nan	0.3333	0.1667
0.0	8.7	2000	nan	0.3333	0.1667
0.0	9.78	2250	nan	0.3333	0.1667
0.0	10.87	2500	nan	0.3333	0.1667
0.0	11.96	2750	nan	0.3333	0.1667
0.0	13.04	3000	nan	0.3333	0.1667
0.0	14.13	3250	nan	0.3333	0.1667
0.0	15.22	3500	nan	0.3333	0.1667
0.0	16.3	3750	nan	0.3333	0.1667
0.0	17.39	4000	nan	0.3333	0.1667
0.0	18.48	4250	nan	0.3333	0.1667
0.0	19.57	4500	nan	0.3333	0.1667
0.0	20.65	4750	nan	0.3333	0.1667
0.0	21.74	5000	nan	0.3333	0.1667
0.0	22.83	5250	nan	0.3333	0.1667
0.0	23.91	5500	nan	0.3333	0.1667
0.0	25.0	5750	nan	0.3333	0.1667
0.0	26.09	6000	nan	0.3333	0.1667
0.0	27.17	6250	nan	0.3333	0.1667
0.0	28.26	6500	nan	0.3333	0.1667
0.0	29.35	6750	nan	0.3333	0.1667

Framework versions

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