scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_155

This model is a fine-tuned version of haryoaw/scenario-MDBT-TCR_data-AmazonScience_massive_all_1_1 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	0.2672	5000	nan	0.0315	0.0010
0.0	0.5344	10000	nan	0.0315	0.0010
0.0	0.8017	15000	nan	0.0315	0.0010
0.0	1.0689	20000	nan	0.0315	0.0010
0.0	1.3361	25000	nan	0.0315	0.0010
0.0	1.6033	30000	nan	0.0315	0.0010
0.0	1.8706	35000	nan	0.0315	0.0010
0.0	2.1378	40000	nan	0.0315	0.0010
0.0	2.4050	45000	nan	0.0315	0.0010
0.0	2.6722	50000	nan	0.0315	0.0010
0.0	2.9394	55000	nan	0.0315	0.0010
0.0	3.2067	60000	nan	0.0315	0.0010
0.0	3.4739	65000	nan	0.0315	0.0010
0.0	3.7411	70000	nan	0.0315	0.0010
0.0	4.0083	75000	nan	0.0315	0.0010
0.0	4.2756	80000	nan	0.0315	0.0010
0.0	4.5428	85000	nan	0.0315	0.0010
0.0	4.8100	90000	nan	0.0315	0.0010
0.0	5.0772	95000	nan	0.0315	0.0010
0.0	5.3444	100000	nan	0.0315	0.0010
0.0	5.6117	105000	nan	0.0315	0.0010
0.0	5.8789	110000	nan	0.0315	0.0010
0.0	6.1461	115000	nan	0.0315	0.0010
0.0	6.4133	120000	nan	0.0315	0.0010
0.0	6.6806	125000	nan	0.0315	0.0010
0.0	6.9478	130000	nan	0.0315	0.0010
0.0	7.2150	135000	nan	0.0315	0.0010
0.0	7.4822	140000	nan	0.0315	0.0010
0.0	7.7495	145000	nan	0.0315	0.0010
0.0	8.0167	150000	nan	0.0315	0.0010
0.0	8.2839	155000	nan	0.0315	0.0010
0.0	8.5511	160000	nan	0.0315	0.0010
0.0	8.8183	165000	nan	0.0315	0.0010
0.0	9.0856	170000	nan	0.0315	0.0010
0.0	9.3528	175000	nan	0.0315	0.0010
0.0	9.6200	180000	nan	0.0315	0.0010
0.0	9.8872	185000	nan	0.0315	0.0010
0.0	10.1545	190000	nan	0.0315	0.0010
0.0	10.4217	195000	nan	0.0315	0.0010
0.0	10.6889	200000	nan	0.0315	0.0010
0.0	10.9561	205000	nan	0.0315	0.0010
0.0	11.2233	210000	nan	0.0315	0.0010
0.0	11.4906	215000	nan	0.0315	0.0010
0.0	11.7578	220000	nan	0.0315	0.0010
0.0	12.0250	225000	nan	0.0315	0.0010
0.0	12.2922	230000	nan	0.0315	0.0010
0.0	12.5595	235000	nan	0.0315	0.0010
0.0	12.8267	240000	nan	0.0315	0.0010
0.0	13.0939	245000	nan	0.0315	0.0010
0.0	13.3611	250000	nan	0.0315	0.0010
0.0	13.6283	255000	nan	0.0315	0.0010
0.0	13.8956	260000	nan	0.0315	0.0010
0.0	14.1628	265000	nan	0.0315	0.0010
0.0	14.4300	270000	nan	0.0315	0.0010
0.0	14.6972	275000	nan	0.0315	0.0010
0.0	14.9645	280000	nan	0.0315	0.0010
0.0	15.2317	285000	nan	0.0315	0.0010
0.0	15.4989	290000	nan	0.0315	0.0010
0.0	15.7661	295000	nan	0.0315	0.0010
0.0	16.0333	300000	nan	0.0315	0.0010
0.0	16.3006	305000	nan	0.0315	0.0010
0.0	16.5678	310000	nan	0.0315	0.0010
0.0	16.8350	315000	nan	0.0315	0.0010
0.0	17.1022	320000	nan	0.0315	0.0010
0.0	17.3695	325000	nan	0.0315	0.0010
0.0	17.6367	330000	nan	0.0315	0.0010
0.0	17.9039	335000	nan	0.0315	0.0010
0.0	18.1711	340000	nan	0.0315	0.0010
0.0	18.4384	345000	nan	0.0315	0.0010
0.0	18.7056	350000	nan	0.0315	0.0010
0.0	18.9728	355000	nan	0.0315	0.0010
0.0	19.2400	360000	nan	0.0315	0.0010
0.0	19.5072	365000	nan	0.0315	0.0010
0.0	19.7745	370000	nan	0.0315	0.0010
0.0	20.0417	375000	nan	0.0315	0.0010
0.0	20.3089	380000	nan	0.0315	0.0010
0.0	20.5761	385000	nan	0.0315	0.0010
0.0	20.8434	390000	nan	0.0315	0.0010
0.0	21.1106	395000	nan	0.0315	0.0010
0.0	21.3778	400000	nan	0.0315	0.0010
0.0	21.6450	405000	nan	0.0315	0.0010
0.0	21.9122	410000	nan	0.0315	0.0010
0.0	22.1795	415000	nan	0.0315	0.0010
0.0	22.4467	420000	nan	0.0315	0.0010
0.0	22.7139	425000	nan	0.0315	0.0010
0.0	22.9811	430000	nan	0.0315	0.0010
0.0	23.2484	435000	nan	0.0315	0.0010
0.0	23.5156	440000	nan	0.0315	0.0010
0.0	23.7828	445000	nan	0.0315	0.0010
0.0	24.0500	450000	nan	0.0315	0.0010
0.0	24.3172	455000	nan	0.0315	0.0010
0.0	24.5845	460000	nan	0.0315	0.0010
0.0	24.8517	465000	nan	0.0315	0.0010
0.0	25.1189	470000	nan	0.0315	0.0010
0.0	25.3861	475000	nan	0.0315	0.0010
0.0	25.6534	480000	nan	0.0315	0.0010
0.0	25.9206	485000	nan	0.0315	0.0010
0.0	26.1878	490000	nan	0.0315	0.0010
0.0	26.4550	495000	nan	0.0315	0.0010
0.0	26.7222	500000	nan	0.0315	0.0010
0.0	26.9895	505000	nan	0.0315	0.0010
0.0	27.2567	510000	nan	0.0315	0.0010
0.0	27.5239	515000	nan	0.0315	0.0010
0.0	27.7911	520000	nan	0.0315	0.0010
0.0	28.0584	525000	nan	0.0315	0.0010
0.0	28.3256	530000	nan	0.0315	0.0010
0.0	28.5928	535000	nan	0.0315	0.0010
0.0	28.8600	540000	nan	0.0315	0.0010
0.0	29.1273	545000	nan	0.0315	0.0010
0.0	29.3945	550000	nan	0.0315	0.0010
0.0	29.6617	555000	nan	0.0315	0.0010
0.0	29.9289	560000	nan	0.0315	0.0010

Framework versions

• Transformers 4.44.2
• Pytorch 2.1.1+cu121
• Datasets 2.14.5
• Tokenizers 0.19.1