scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma

This model is a fine-tuned version of haryoaw/scenario-TCR_data-cl-cardiff_cl_only2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 5.6776
• Accuracy: 0.4560
• F1: 0.4557

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	1.7114	0.4745	0.4746
0.5344	2.17	500	2.4454	0.4522	0.4441
0.5344	3.26	750	2.7492	0.4699	0.4693
0.2322	4.35	1000	3.0156	0.4336	0.4123
0.2322	5.43	1250	2.9947	0.4799	0.4819
0.1279	6.52	1500	3.7528	0.4506	0.4474
0.1279	7.61	1750	3.5806	0.4560	0.4560
0.0973	8.7	2000	3.8704	0.4545	0.4510
0.0973	9.78	2250	4.0113	0.4498	0.4450
0.0683	10.87	2500	3.5910	0.4676	0.4690
0.0683	11.96	2750	4.3665	0.4506	0.4480
0.0498	13.04	3000	4.2188	0.4799	0.4809
0.0498	14.13	3250	4.8550	0.4398	0.4315
0.0324	15.22	3500	4.7206	0.4630	0.4586
0.0324	16.3	3750	5.0101	0.4444	0.4392
0.025	17.39	4000	5.0926	0.4660	0.4667
0.025	18.48	4250	4.8167	0.4869	0.4886
0.0248	19.57	4500	5.1087	0.4606	0.4610
0.0248	20.65	4750	5.4661	0.4429	0.4365
0.0154	21.74	5000	5.2199	0.4730	0.4742
0.0154	22.83	5250	5.1442	0.4807	0.4825
0.0112	23.91	5500	5.4588	0.4691	0.4696
0.0112	25.0	5750	5.4026	0.4653	0.4654
0.0112	26.09	6000	5.6362	0.4506	0.4466
0.0112	27.17	6250	5.5405	0.4614	0.4620
0.0046	28.26	6500	5.6038	0.4591	0.4590
0.0046	29.35	6750	5.6776	0.4560	0.4557

Framework versions

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