scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_155

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the massive dataset. It achieves the following results on the evaluation set:

• Loss: nan
• Accuracy: 0.0315
• F1: 0.0010

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: 55
• 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
0.0	0.27	5000	nan	0.0315	0.0010
0.0	0.53	10000	nan	0.0315	0.0010
0.0	0.8	15000	nan	0.0315	0.0010
0.0	1.07	20000	nan	0.0315	0.0010
0.0	1.34	25000	nan	0.0315	0.0010
0.0	1.6	30000	nan	0.0315	0.0010
0.0	1.87	35000	nan	0.0315	0.0010
0.0	2.14	40000	nan	0.0315	0.0010
0.0	2.41	45000	nan	0.0315	0.0010
0.0	2.67	50000	nan	0.0315	0.0010
0.0	2.94	55000	nan	0.0315	0.0010
0.0	3.21	60000	nan	0.0315	0.0010
0.0	3.47	65000	nan	0.0315	0.0010
0.0	3.74	70000	nan	0.0315	0.0010
0.0	4.01	75000	nan	0.0315	0.0010
0.0	4.28	80000	nan	0.0315	0.0010
0.0	4.54	85000	nan	0.0315	0.0010
0.0	4.81	90000	nan	0.0315	0.0010
0.0	5.08	95000	nan	0.0315	0.0010
0.0	5.34	100000	nan	0.0315	0.0010
0.0	5.61	105000	nan	0.0315	0.0010
0.0	5.88	110000	nan	0.0315	0.0010
0.0	6.15	115000	nan	0.0315	0.0010
0.0	6.41	120000	nan	0.0315	0.0010
0.0	6.68	125000	nan	0.0315	0.0010
0.0	6.95	130000	nan	0.0315	0.0010
0.0	7.22	135000	nan	0.0315	0.0010
0.0	7.48	140000	nan	0.0315	0.0010
0.0	7.75	145000	nan	0.0315	0.0010
0.0	8.02	150000	nan	0.0315	0.0010
0.0	8.28	155000	nan	0.0315	0.0010
0.0	8.55	160000	nan	0.0315	0.0010
0.0	8.82	165000	nan	0.0315	0.0010
0.0	9.09	170000	nan	0.0315	0.0010
0.0	9.35	175000	nan	0.0315	0.0010
0.0	9.62	180000	nan	0.0315	0.0010
0.0	9.89	185000	nan	0.0315	0.0010
0.0	10.15	190000	nan	0.0315	0.0010
0.0	10.42	195000	nan	0.0315	0.0010
0.0	10.69	200000	nan	0.0315	0.0010
0.0	10.96	205000	nan	0.0315	0.0010
0.0	11.22	210000	nan	0.0315	0.0010
0.0	11.49	215000	nan	0.0315	0.0010
0.0	11.76	220000	nan	0.0315	0.0010
0.0	12.03	225000	nan	0.0315	0.0010
0.0	12.29	230000	nan	0.0315	0.0010
0.0	12.56	235000	nan	0.0315	0.0010
0.0	12.83	240000	nan	0.0315	0.0010
0.0	13.09	245000	nan	0.0315	0.0010
0.0	13.36	250000	nan	0.0315	0.0010
0.0	13.63	255000	nan	0.0315	0.0010
0.0	13.9	260000	nan	0.0315	0.0010
0.0	14.16	265000	nan	0.0315	0.0010
0.0	14.43	270000	nan	0.0315	0.0010
0.0	14.7	275000	nan	0.0315	0.0010
0.0	14.96	280000	nan	0.0315	0.0010
0.0	15.23	285000	nan	0.0315	0.0010
0.0	15.5	290000	nan	0.0315	0.0010
0.0	15.77	295000	nan	0.0315	0.0010
0.0	16.03	300000	nan	0.0315	0.0010
0.0	16.3	305000	nan	0.0315	0.0010
0.0	16.57	310000	nan	0.0315	0.0010
0.0	16.84	315000	nan	0.0315	0.0010
0.0	17.1	320000	nan	0.0315	0.0010
0.0	17.37	325000	nan	0.0315	0.0010
0.0	17.64	330000	nan	0.0315	0.0010
0.0	17.9	335000	nan	0.0315	0.0010
0.0	18.17	340000	nan	0.0315	0.0010
0.0	18.44	345000	nan	0.0315	0.0010
0.0	18.71	350000	nan	0.0315	0.0010
0.0	18.97	355000	nan	0.0315	0.0010
0.0	19.24	360000	nan	0.0315	0.0010
0.0	19.51	365000	nan	0.0315	0.0010
0.0	19.77	370000	nan	0.0315	0.0010
0.0	20.04	375000	nan	0.0315	0.0010
0.0	20.31	380000	nan	0.0315	0.0010
0.0	20.58	385000	nan	0.0315	0.0010
0.0	20.84	390000	nan	0.0315	0.0010
0.0	21.11	395000	nan	0.0315	0.0010
0.0	21.38	400000	nan	0.0315	0.0010
0.0	21.65	405000	nan	0.0315	0.0010
0.0	21.91	410000	nan	0.0315	0.0010
0.0	22.18	415000	nan	0.0315	0.0010
0.0	22.45	420000	nan	0.0315	0.0010
0.0	22.71	425000	nan	0.0315	0.0010
0.0	22.98	430000	nan	0.0315	0.0010
0.0	23.25	435000	nan	0.0315	0.0010
0.0	23.52	440000	nan	0.0315	0.0010
0.0	23.78	445000	nan	0.0315	0.0010
0.0	24.05	450000	nan	0.0315	0.0010
0.0	24.32	455000	nan	0.0315	0.0010
0.0	24.58	460000	nan	0.0315	0.0010
0.0	24.85	465000	nan	0.0315	0.0010
0.0	25.12	470000	nan	0.0315	0.0010
0.0	25.39	475000	nan	0.0315	0.0010
0.0	25.65	480000	nan	0.0315	0.0010
0.0	25.92	485000	nan	0.0315	0.0010
0.0	26.19	490000	nan	0.0315	0.0010
0.0	26.46	495000	nan	0.0315	0.0010
0.0	26.72	500000	nan	0.0315	0.0010
0.0	26.99	505000	nan	0.0315	0.0010
0.0	27.26	510000	nan	0.0315	0.0010
0.0	27.52	515000	nan	0.0315	0.0010
0.0	27.79	520000	nan	0.0315	0.0010
0.0	28.06	525000	nan	0.0315	0.0010
0.0	28.33	530000	nan	0.0315	0.0010
0.0	28.59	535000	nan	0.0315	0.0010
0.0	28.86	540000	nan	0.0315	0.0010
0.0	29.13	545000	nan	0.0315	0.0010
0.0	29.39	550000	nan	0.0315	0.0010
0.0	29.66	555000	nan	0.0315	0.0010
0.0	29.93	560000	nan	0.0315	0.0010

Framework versions

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