taylor-swift-model-temp

This model is a fine-tuned version of distilgpt2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 3.1118

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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss
4.0072	1.0	58	3.7794
3.8685	2.0	116	3.6857
3.8123	3.0	174	3.6220
3.7141	4.0	232	3.5796
3.3674	5.0	290	3.5402
3.556	6.0	348	3.5092
3.442	7.0	406	3.4829
3.5147	8.0	464	3.4609
3.3591	9.0	522	3.4289
3.3258	10.0	580	3.4135
3.2393	11.0	638	3.3918
3.2989	12.0	696	3.3756
3.2535	13.0	754	3.3557
3.1144	14.0	812	3.3352
2.9332	15.0	870	3.3305
3.0371	16.0	928	3.3078
3.0357	17.0	986	3.2889
2.8728	18.0	1044	3.2851
2.9121	19.0	1102	3.2688
2.9804	20.0	1160	3.2562
2.855	21.0	1218	3.2485
2.7546	22.0	1276	3.2275
2.9248	23.0	1334	3.2233
2.9627	24.0	1392	3.2113
2.891	25.0	1450	3.1965
2.7106	26.0	1508	3.1925
2.8863	27.0	1566	3.1836
2.8311	28.0	1624	3.1869
2.6953	29.0	1682	3.1769
2.7916	30.0	1740	3.1717
2.7262	31.0	1798	3.1609
2.6203	32.0	1856	3.1564
2.7066	33.0	1914	3.1492
2.3818	34.0	1972	3.1475
2.7237	35.0	2030	3.1412
2.4593	36.0	2088	3.1372
2.5471	37.0	2146	3.1298
2.6026	38.0	2204	3.1324
2.5049	39.0	2262	3.1285
2.5509	40.0	2320	3.1262
2.7736	41.0	2378	3.1142
2.7144	42.0	2436	3.1159
2.5972	43.0	2494	3.1145
2.5897	44.0	2552	3.1142
2.4131	45.0	2610	3.1152
2.5602	46.0	2668	3.1130
2.4986	47.0	2726	3.1123
2.5507	48.0	2784	3.1108
2.4885	49.0	2842	3.1124
2.4204	50.0	2900	3.1118

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.8.0
• Tokenizers 0.13.2