stlenc

saracandu/stlenc

stlenc is a feature extraction model from saracandu. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Feature Extraction
Library: transformers
License: mit
Model type: stl_encoder
Access: Public
Created: Dec 21, 2025
Updated: Dec 24, 2025
SHA: 26909ccc

Model card

From the Hugging Face model README

stlenc

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

Loss: 0.0125
Mse Sync: 0.0125
Cosine Similarity: 0.6938

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: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Mse Sync	Cosine Similarity
0.0247	0.0203	100	0.0222	0.0222	0.4734
0.0247	0.0407	200	0.0205	0.0205	0.5004
0.0242	0.0610	300	0.0208	0.0208	0.4881
0.0258	0.0813	400	0.0202	0.0202	0.5144
0.0236	0.1016	500	0.0202	0.0202	0.5102
0.023	0.1220	600	0.0198	0.0198	0.5193
0.0228	0.1423	700	0.0210	0.0210	0.5076
0.0245	0.1626	800	0.0197	0.0197	0.5135
0.0229	0.1829	900	0.0200	0.0200	0.5133
0.0213	0.2033	1000	0.0200	0.0200	0.5050
0.0224	0.2236	1100	0.0196	0.0196	0.5187
0.0235	0.2439	1200	0.0198	0.0198	0.5165
0.0216	0.2642	1300	0.0195	0.0195	0.5210
0.0227	0.2846	1400	0.0201	0.0201	0.5162
0.0216	0.3049	1500	0.0191	0.0191	0.5348
0.0207	0.3252	1600	0.0196	0.0196	0.5202
0.0209	0.3455	1700	0.0193	0.0193	0.5231
0.0218	0.3659	1800	0.0193	0.0193	0.5317
0.0226	0.3862	1900	0.0193	0.0193	0.5275
0.0214	0.4065	2000	0.0194	0.0194	0.5242
0.0211	0.4268	2100	0.0192	0.0192	0.5301
0.021	0.4472	2200	0.0196	0.0196	0.5214
0.0215	0.4675	2300	0.0190	0.0190	0.5339
0.0205	0.4878	2400	0.0187	0.0187	0.5438
0.0207	0.5081	2500	0.0188	0.0188	0.5425
0.0207	0.5285	2600	0.0190	0.0190	0.5422
0.0203	0.5488	2700	0.0194	0.0194	0.5413
0.0214	0.5691	2800	0.0192	0.0192	0.5390
0.0202	0.5894	2900	0.0186	0.0186	0.5509
0.0196	0.6098	3000	0.0192	0.0192	0.5456
0.0201	0.6301	3100	0.0185	0.0185	0.5504
0.0203	0.6504	3200	0.0202	0.0202	0.5340
0.0194	0.6707	3300	0.0184	0.0184	0.5512
0.0205	0.6911	3400	0.0188	0.0188	0.5340
0.0201	0.7114	3500	0.0186	0.0186	0.5504
0.0206	0.7317	3600	0.0190	0.0190	0.5409
0.0194	0.7520	3700	0.0183	0.0183	0.5600
0.02	0.7724	3800	0.0187	0.0187	0.5567
0.0209	0.7927	3900	0.0185	0.0185	0.5464
0.0191	0.8130	4000	0.0185	0.0185	0.5530
0.0199	0.8333	4100	0.0186	0.0186	0.5472
0.0191	0.8537	4200	0.0182	0.0182	0.5595
0.0206	0.8740	4300	0.0191	0.0191	0.5430
0.0205	0.8943	4400	0.0182	0.0182	0.5597
0.0201	0.9146	4500	0.0185	0.0185	0.5521
0.0215	0.9350	4600	0.0188	0.0188	0.5417
0.02	0.9553	4700	0.0186	0.0186	0.5534
0.0208	0.9756	4800	0.0187	0.0187	0.5475
0.0194	0.9959	4900	0.0183	0.0183	0.5611
0.0187	1.0163	5000	0.0191	0.0191	0.5489
0.0203	1.0366	5100	0.0194	0.0194	0.5413
0.0192	1.0569	5200	0.0185	0.0185	0.5580
0.02	1.0772	5300	0.0196	0.0196	0.5371
0.0198	1.0976	5400	0.0182	0.0182	0.5592
0.0198	1.1179	5500	0.0182	0.0182	0.5592
0.0191	1.1382	5600	0.0185	0.0185	0.5529
0.0191	1.1585	5700	0.0182	0.0182	0.5608
0.0195	1.1789	5800	0.0181	0.0181	0.5604
0.0198	1.1992	5900	0.0183	0.0183	0.5586
0.0193	1.2195	6000	0.0185	0.0185	0.5537
0.0205	1.2398	6100	0.0182	0.0182	0.5658
0.0195	1.2602	6200	0.0180	0.0180	0.5636
0.0197	1.2805	6300	0.0180	0.0180	0.5680
0.0205	1.3008	6400	0.0182	0.0182	0.5605
0.0198	1.3211	6500	0.0185	0.0185	0.5548
0.02	1.3415	6600	0.0183	0.0183	0.5558
0.0196	1.3618	6700	0.0180	0.0180	0.5626
0.0199	1.3821	6800	0.0184	0.0184	0.5552
0.0194	1.4024	6900	0.0185	0.0185	0.5627
0.019	1.4228	7000	0.0180	0.0180	0.5654
0.0191	1.4431	7100	0.0180	0.0180	0.5646
0.0202	1.4634	7200	0.0183	0.0183	0.5625
0.0192	1.4837	7300	0.0187	0.0187	0.5589
0.0202	1.5041	7400	0.0180	0.0180	0.5597
0.02	1.5244	7500	0.0183	0.0183	0.5602
0.0201	1.5447	7600	0.0178	0.0178	0.5695
0.0192	1.5650	7700	0.0178	0.0178	0.5697
0.0179	1.5854	7800	0.0178	0.0178	0.5688
0.0177	1.6057	7900	0.0181	0.0181	0.5636
0.0192	1.6260	8000	0.0179	0.0179	0.5680
0.0195	1.6463	8100	0.0180	0.0180	0.5637
0.0185	1.6667	8200	0.0179	0.0179	0.5609
0.0191	1.6870	8300	0.0177	0.0177	0.5723
0.0185	1.7073	8400	0.0176	0.0176	0.5735
0.019	1.7276	8500	0.0178	0.0178	0.5695
0.0187	1.7480	8600	0.0175	0.0175	0.5768
0.0168	1.7683	8700	0.0173	0.0173	0.5776
0.0168	1.7886	8800	0.0169	0.0169	0.5865
0.0178	1.8089	8900	0.0170	0.0170	0.5886
0.0175	1.8293	9000	0.0171	0.0171	0.5932
0.0175	1.8496	9100	0.0175	0.0175	0.5744
0.0169	1.8699	9200	0.0168	0.0168	0.5952
0.0183	1.8902	9300	0.0166	0.0166	0.6016
0.0162	1.9106	9400	0.0164	0.0164	0.6034
0.0167	1.9309	9500	0.0163	0.0163	0.6039
0.0167	1.9512	9600	0.0166	0.0166	0.6031
0.0166	1.9715	9700	0.0163	0.0163	0.6064
0.0169	1.9919	9800	0.0165	0.0165	0.6034
0.0162	2.0122	9900	0.0161	0.0161	0.6103
0.016	2.0325	10000	0.0167	0.0167	0.6069
0.0152	2.0528	10100	0.0163	0.0163	0.6030
0.016	2.0732	10200	0.0158	0.0158	0.6184
0.0161	2.0935	10300	0.0160	0.0160	0.6165
0.0167	2.1138	10400	0.0156	0.0156	0.6176
0.0155	2.1341	10500	0.0158	0.0158	0.6212
0.0144	2.1545	10600	0.0156	0.0156	0.6219
0.0145	2.1748	10700	0.0160	0.0160	0.6131
0.0158	2.1951	10800	0.0161	0.0161	0.6085
0.0159	2.2154	10900	0.0156	0.0156	0.6200
0.0143	2.2358	11000	0.0156	0.0156	0.6192
0.0158	2.2561	11100	0.0158	0.0158	0.6173
0.015	2.2764	11200	0.0157	0.0157	0.6234
0.0156	2.2967	11300	0.0153	0.0153	0.6251
0.0143	2.3171	11400	0.0155	0.0155	0.6215
0.0159	2.3374	11500	0.0159	0.0159	0.6101
0.0155	2.3577	11600	0.0155	0.0155	0.6292
0.0145	2.3780	11700	0.0153	0.0153	0.6271
0.014	2.3984	11800	0.0152	0.0152	0.6296
0.0154	2.4187	11900	0.0151	0.0151	0.6282
0.0155	2.4390	12000	0.0154	0.0154	0.6190
0.0151	2.4593	12100	0.0158	0.0158	0.6152
0.0156	2.4797	12200	0.0152	0.0152	0.6301
0.0148	2.5	12300	0.0150	0.0150	0.6332
0.0148	2.5203	12400	0.0149	0.0149	0.6326
0.0161	2.5407	12500	0.0154	0.0154	0.6279
0.0143	2.5610	12600	0.0148	0.0148	0.6392
0.0143	2.5813	12700	0.0151	0.0151	0.6325
0.0141	2.6016	12800	0.0154	0.0154	0.6281
0.0148	2.6220	12900	0.0149	0.0149	0.6323
0.016	2.6423	13000	0.0155	0.0155	0.6230
0.0154	2.6626	13100	0.0156	0.0156	0.6211
0.0147	2.6829	13200	0.0151	0.0151	0.6320
0.0152	2.7033	13300	0.0153	0.0153	0.6253
0.0153	2.7236	13400	0.0155	0.0155	0.6275
0.0153	2.7439	13500	0.0147	0.0147	0.6431
0.0148	2.7642	13600	0.0154	0.0154	0.6322
0.0134	2.7846	13700	0.0153	0.0153	0.6272
0.0165	2.8049	13800	0.0149	0.0149	0.6357
0.014	2.8252	13900	0.0150	0.0150	0.6340
0.014	2.8455	14000	0.0149	0.0149	0.6318
0.0145	2.8659	14100	0.0151	0.0151	0.6353
0.0139	2.8862	14200	0.0149	0.0149	0.6367
0.0155	2.9065	14300	0.0151	0.0151	0.6354
0.015	2.9268	14400	0.0146	0.0146	0.6405
0.0145	2.9472	14500	0.0149	0.0149	0.6368
0.0142	2.9675	14600	0.0150	0.0150	0.6296
0.015	2.9878	14700	0.0147	0.0147	0.6433
0.0155	3.0081	14800	0.0147	0.0147	0.6400
0.0147	3.0285	14900	0.0146	0.0146	0.6363
0.0127	3.0488	15000	0.0147	0.0147	0.6406
0.0132	3.0691	15100	0.0146	0.0146	0.6417
0.014	3.0894	15200	0.0146	0.0146	0.6375
0.0139	3.1098	15300	0.0146	0.0146	0.6435
0.0152	3.1301	15400	0.0149	0.0149	0.6333
0.0145	3.1504	15500	0.0146	0.0146	0.6417
0.0136	3.1707	15600	0.0145	0.0145	0.6467
0.0143	3.1911	15700	0.0149	0.0149	0.6386
0.014	3.2114	15800	0.0147	0.0147	0.6458
0.0142	3.2317	15900	0.0143	0.0143	0.6479
0.0137	3.2520	16000	0.0148	0.0148	0.6387
0.0135	3.2724	16100	0.0147	0.0147	0.6394
0.0151	3.2927	16200	0.0144	0.0144	0.6465
0.0154	3.3130	16300	0.0142	0.0142	0.6553
0.0139	3.3333	16400	0.0149	0.0149	0.6360
0.0137	3.3537	16500	0.0145	0.0145	0.6458
0.0141	3.3740	16600	0.0145	0.0145	0.6468
0.0139	3.3943	16700	0.0148	0.0148	0.6402
0.0132	3.4146	16800	0.0149	0.0149	0.6424
0.0133	3.4350	16900	0.0147	0.0147	0.6423
0.0137	3.4553	17000	0.0143	0.0143	0.6493
0.0142	3.4756	17100	0.0146	0.0146	0.6462
0.0138	3.4959	17200	0.0143	0.0143	0.6470
0.0149	3.5163	17300	0.0145	0.0145	0.6511
0.0148	3.5366	17400	0.0145	0.0145	0.6469
0.0138	3.5569	17500	0.0144	0.0144	0.6437
0.0136	3.5772	17600	0.0143	0.0143	0.6526
0.0139	3.5976	17700	0.0143	0.0143	0.6494
0.0126	3.6179	17800	0.0143	0.0143	0.6523
0.0127	3.6382	17900	0.0144	0.0144	0.6456
0.0133	3.6585	18000	0.0143	0.0143	0.6499
0.0141	3.6789	18100	0.0142	0.0142	0.6527
0.0124	3.6992	18200	0.0146	0.0146	0.6429
0.0139	3.7195	18300	0.0142	0.0142	0.6493
0.0141	3.7398	18400	0.0142	0.0142	0.6512
0.0132	3.7602	18500	0.0143	0.0143	0.6490
0.0141	3.7805	18600	0.0144	0.0144	0.6432
0.0131	3.8008	18700	0.0142	0.0142	0.6519
0.0135	3.8211	18800	0.0147	0.0147	0.6442
0.0149	3.8415	18900	0.0147	0.0147	0.6422
0.0141	3.8618	19000	0.0142	0.0142	0.6547
0.0132	3.8821	19100	0.0143	0.0143	0.6489
0.0141	3.9024	19200	0.0143	0.0143	0.6494
0.0123	3.9228	19300	0.0140	0.0140	0.6559
0.0139	3.9431	19400	0.0142	0.0142	0.6535
0.0138	3.9634	19500	0.0144	0.0144	0.6457
0.0131	3.9837	19600	0.0142	0.0142	0.6477
0.0128	4.0041	19700	0.0145	0.0145	0.6453
0.0128	4.0244	19800	0.0142	0.0142	0.6516
0.0127	4.0447	19900	0.0141	0.0141	0.6517
0.0137	4.0650	20000	0.0147	0.0147	0.6458
0.0137	4.0854	20100	0.0142	0.0142	0.6535
0.013	4.1057	20200	0.0146	0.0146	0.6506
0.0134	4.1260	20300	0.0149	0.0149	0.6443
0.0135	4.1463	20400	0.0145	0.0145	0.6495
0.0139	4.1667	20500	0.0140	0.0140	0.6597
0.014	4.1870	20600	0.0147	0.0147	0.6421
0.0135	4.2073	20700	0.0145	0.0145	0.6438
0.0127	4.2276	20800	0.0143	0.0143	0.6502
0.0124	4.2480	20900	0.0141	0.0141	0.6558
0.0139	4.2683	21000	0.0143	0.0143	0.6509
0.013	4.2886	21100	0.0141	0.0141	0.6591
0.0129	4.3089	21200	0.0143	0.0143	0.6497
0.0122	4.3293	21300	0.0148	0.0148	0.6440
0.0135	4.3496	21400	0.0142	0.0142	0.6550
0.0117	4.3699	21500	0.0142	0.0142	0.6516
0.0105	4.3902	21600	0.0146	0.0146	0.6420
0.0142	4.4106	21700	0.0146	0.0146	0.6451
0.0132	4.4309	21800	0.0143	0.0143	0.6504
0.0134	4.4512	21900	0.0139	0.0139	0.6580
0.0107	4.4715	22000	0.0147	0.0147	0.6431
0.0133	4.4919	22100	0.0142	0.0142	0.6533
0.0124	4.5122	22200	0.0141	0.0141	0.6564
0.011	4.5325	22300	0.0139	0.0139	0.6608
0.011	4.5528	22400	0.0141	0.0141	0.6551
0.0131	4.5732	22500	0.0144	0.0144	0.6532
0.0112	4.5935	22600	0.0143	0.0143	0.6521
0.0116	4.6138	22700	0.0140	0.0140	0.6558
0.01	4.6341	22800	0.0143	0.0143	0.6469
0.0112	4.6545	22900	0.0141	0.0141	0.6540
0.0115	4.6748	23000	0.0140	0.0140	0.6519
0.0107	4.6951	23100	0.0141	0.0141	0.6545
0.011	4.7154	23200	0.0141	0.0141	0.6525
0.0119	4.7358	23300	0.0139	0.0139	0.6609
0.013	4.7561	23400	0.0138	0.0138	0.6587
0.0107	4.7764	23500	0.0136	0.0136	0.6665
0.0111	4.7967	23600	0.0136	0.0136	0.6634
0.0111	4.8171	23700	0.0140	0.0140	0.6565
0.0106	4.8374	23800	0.0139	0.0139	0.6587
0.0114	4.8577	23900	0.0140	0.0140	0.6575
0.011	4.8780	24000	0.0142	0.0142	0.6575
0.0115	4.8984	24100	0.0139	0.0139	0.6612
0.012	4.9187	24200	0.0136	0.0136	0.6683
0.0123	4.9390	24300	0.0137	0.0137	0.6659
0.0118	4.9593	24400	0.0144	0.0144	0.6548
0.01	4.9797	24500	0.0140	0.0140	0.6594
0.0112	5.0	24600	0.0136	0.0136	0.6662
0.0108	5.0203	24700	0.0140	0.0140	0.6605
0.0103	5.0407	24800	0.0138	0.0138	0.6636
0.0124	5.0610	24900	0.0137	0.0137	0.6645
0.0116	5.0813	25000	0.0141	0.0141	0.6558
0.009	5.1016	25100	0.0138	0.0138	0.6637
0.0111	5.1220	25200	0.0140	0.0140	0.6594
0.0119	5.1423	25300	0.0139	0.0139	0.6584
0.011	5.1626	25400	0.0138	0.0138	0.6649
0.0111	5.1829	25500	0.0137	0.0137	0.6660
0.0115	5.2033	25600	0.0138	0.0138	0.6654
0.0113	5.2236	25700	0.0138	0.0138	0.6615
0.01	5.2439	25800	0.0142	0.0142	0.6558
0.0114	5.2642	25900	0.0137	0.0137	0.6656
0.0097	5.2846	26000	0.0138	0.0138	0.6620
0.0094	5.3049	26100	0.0136	0.0136	0.6663
0.0111	5.3252	26200	0.0137	0.0137	0.6638
0.0114	5.3455	26300	0.0142	0.0142	0.6554
0.0107	5.3659	26400	0.0137	0.0137	0.6619
0.0115	5.3862	26500	0.0137	0.0137	0.6645
0.0112	5.4065	26600	0.0134	0.0134	0.6712
0.0106	5.4268	26700	0.0134	0.0134	0.6691
0.011	5.4472	26800	0.0134	0.0134	0.6713
0.0116	5.4675	26900	0.0136	0.0136	0.6682
0.0111	5.4878	27000	0.0134	0.0134	0.6695
0.0111	5.5081	27100	0.0136	0.0136	0.6686
0.0106	5.5285	27200	0.0135	0.0135	0.6719
0.011	5.5488	27300	0.0138	0.0138	0.6628
0.0094	5.5691	27400	0.0135	0.0135	0.6687
0.0102	5.5894	27500	0.0138	0.0138	0.6641
0.0104	5.6098	27600	0.0135	0.0135	0.6703
0.01	5.6301	27700	0.0136	0.0136	0.6708
0.0104	5.6504	27800	0.0136	0.0136	0.6688
0.0102	5.6707	27900	0.0136	0.0136	0.6682
0.0108	5.6911	28000	0.0138	0.0138	0.6614
0.0108	5.7114	28100	0.0135	0.0135	0.6716
0.0103	5.7317	28200	0.0137	0.0137	0.6650
0.0105	5.7520	28300	0.0136	0.0136	0.6679
0.0108	5.7724	28400	0.0135	0.0135	0.6693
0.0102	5.7927	28500	0.0133	0.0133	0.6745
0.0111	5.8130	28600	0.0133	0.0133	0.6745
0.0102	5.8333	28700	0.0134	0.0134	0.6703
0.0087	5.8537	28800	0.0137	0.0137	0.6660
0.0114	5.8740	28900	0.0136	0.0136	0.6686
0.0114	5.8943	29000	0.0134	0.0134	0.6739
0.0098	5.9146	29100	0.0134	0.0134	0.6724
0.0097	5.9350	29200	0.0132	0.0132	0.6767
0.0108	5.9553	29300	0.0131	0.0131	0.6803
0.0106	5.9756	29400	0.0132	0.0132	0.6775
0.0112	5.9959	29500	0.0133	0.0133	0.6763
0.0096	6.0163	29600	0.0134	0.0134	0.6706
0.0105	6.0366	29700	0.0141	0.0141	0.6561
0.0115	6.0569	29800	0.0132	0.0132	0.6745
0.01	6.0772	29900	0.0132	0.0132	0.6782
0.0114	6.0976	30000	0.0133	0.0133	0.6737
0.0116	6.1179	30100	0.0132	0.0132	0.6771
0.0095	6.1382	30200	0.0135	0.0135	0.6688
0.01	6.1585	30300	0.0134	0.0134	0.6682
0.01	6.1789	30400	0.0132	0.0132	0.6756
0.0106	6.1992	30500	0.0134	0.0134	0.6726
0.0092	6.2195	30600	0.0131	0.0131	0.6755
0.0117	6.2398	30700	0.0133	0.0133	0.6723
0.0098	6.2602	30800	0.0131	0.0131	0.6748
0.0103	6.2805	30900	0.0132	0.0132	0.6757
0.0097	6.3008	31000	0.0135	0.0135	0.6682
0.0103	6.3211	31100	0.0134	0.0134	0.6726
0.0101	6.3415	31200	0.0134	0.0134	0.6712
0.0107	6.3618	31300	0.0132	0.0132	0.6773
0.01	6.3821	31400	0.0133	0.0133	0.6740
0.0097	6.4024	31500	0.0136	0.0136	0.6704
0.0108	6.4228	31600	0.0132	0.0132	0.6764
0.0104	6.4431	31700	0.0131	0.0131	0.6784
0.0123	6.4634	31800	0.0133	0.0133	0.6725
0.0097	6.4837	31900	0.0134	0.0134	0.6703
0.0097	6.5041	32000	0.0133	0.0133	0.6725
0.009	6.5244	32100	0.0130	0.0130	0.6829
0.0116	6.5447	32200	0.0133	0.0133	0.6731
0.0099	6.5650	32300	0.0132	0.0132	0.6760
0.0108	6.5854	32400	0.0133	0.0133	0.6754
0.0103	6.6057	32500	0.0136	0.0136	0.6701
0.0092	6.6260	32600	0.0132	0.0132	0.6782
0.0105	6.6463	32700	0.0130	0.0130	0.6814
0.011	6.6667	32800	0.0133	0.0133	0.6734
0.0102	6.6870	32900	0.0132	0.0132	0.6750
0.0103	6.7073	33000	0.0132	0.0132	0.6766
0.0112	6.7276	33100	0.0131	0.0131	0.6788
0.0089	6.7480	33200	0.0131	0.0131	0.6773
0.0103	6.7683	33300	0.0131	0.0131	0.6752
0.0109	6.7886	33400	0.0133	0.0133	0.6761
0.0078	6.8089	33500	0.0131	0.0131	0.6778
0.011	6.8293	33600	0.0130	0.0130	0.6823
0.0085	6.8496	33700	0.0129	0.0129	0.6815
0.009	6.8699	33800	0.0131	0.0131	0.6770
0.0093	6.8902	33900	0.0131	0.0131	0.6769
0.01	6.9106	34000	0.0132	0.0132	0.6750
0.0097	6.9309	34100	0.0131	0.0131	0.6791
0.0107	6.9512	34200	0.0130	0.0130	0.6824
0.0099	6.9715	34300	0.0130	0.0130	0.6815
0.0095	6.9919	34400	0.0130	0.0130	0.6822
0.01	7.0122	34500	0.0129	0.0129	0.6827
0.0097	7.0325	34600	0.0131	0.0131	0.6801
0.0099	7.0528	34700	0.0129	0.0129	0.6843
0.0085	7.0732	34800	0.0132	0.0132	0.6774
0.0098	7.0935	34900	0.0131	0.0131	0.6780
0.0103	7.1138	35000	0.0130	0.0130	0.6811
0.0104	7.1341	35100	0.0127	0.0127	0.6857
0.0094	7.1545	35200	0.0130	0.0130	0.6812
0.0104	7.1748	35300	0.0132	0.0132	0.6768
0.0092	7.1951	35400	0.0130	0.0130	0.6819
0.0099	7.2154	35500	0.0130	0.0130	0.6810
0.0103	7.2358	35600	0.0132	0.0132	0.6791
0.0103	7.2561	35700	0.0135	0.0135	0.6734
0.0081	7.2764	35800	0.0133	0.0133	0.6753
0.0079	7.2967	35900	0.0131	0.0131	0.6788
0.009	7.3171	36000	0.0130	0.0130	0.6826
0.0096	7.3374	36100	0.0130	0.0130	0.6829
0.0103	7.3577	36200	0.0132	0.0132	0.6821
0.0098	7.3780	36300	0.0130	0.0130	0.6821
0.0102	7.3984	36400	0.0130	0.0130	0.6830
0.0093	7.4187	36500	0.0133	0.0133	0.6756
0.0107	7.4390	36600	0.0131	0.0131	0.6801
0.01	7.4593	36700	0.0128	0.0128	0.6862
0.0101	7.4797	36800	0.0132	0.0132	0.6817
0.0088	7.5	36900	0.0130	0.0130	0.6823
0.0097	7.5203	37000	0.0130	0.0130	0.6828
0.0087	7.5407	37100	0.0129	0.0129	0.6859
0.008	7.5610	37200	0.0129	0.0129	0.6848
0.0096	7.5813	37300	0.0128	0.0128	0.6869
0.0092	7.6016	37400	0.0128	0.0128	0.6856
0.0101	7.6220	37500	0.0130	0.0130	0.6827
0.0102	7.6423	37600	0.0130	0.0130	0.6792
0.0097	7.6626	37700	0.0129	0.0129	0.6806
0.0106	7.6829	37800	0.0128	0.0128	0.6852
0.0087	7.7033	37900	0.0129	0.0129	0.6847
0.0091	7.7236	38000	0.0129	0.0129	0.6851
0.0099	7.7439	38100	0.0128	0.0128	0.6845
0.0094	7.7642	38200	0.0128	0.0128	0.6857
0.0097	7.7846	38300	0.0128	0.0128	0.6858
0.0108	7.8049	38400	0.0127	0.0127	0.6855
0.011	7.8252	38500	0.0128	0.0128	0.6836
0.0088	7.8455	38600	0.0129	0.0129	0.6826
0.0093	7.8659	38700	0.0131	0.0131	0.6796
0.0096	7.8862	38800	0.0129	0.0129	0.6830
0.0089	7.9065	38900	0.0128	0.0128	0.6855
0.0088	7.9268	39000	0.0128	0.0128	0.6879
0.0088	7.9472	39100	0.0127	0.0127	0.6897
0.0088	7.9675	39200	0.0129	0.0129	0.6840
0.0102	7.9878	39300	0.0127	0.0127	0.6878
0.008	8.0081	39400	0.0128	0.0128	0.6867
0.0106	8.0285	39500	0.0130	0.0130	0.6817
0.0089	8.0488	39600	0.0129	0.0129	0.6838
0.0084	8.0691	39700	0.0129	0.0129	0.6847
0.0089	8.0894	39800	0.0128	0.0128	0.6860
0.0095	8.1098	39900	0.0128	0.0128	0.6851
0.0085	8.1301	40000	0.0127	0.0127	0.6872
0.0084	8.1504	40100	0.0129	0.0129	0.6840
0.0084	8.1707	40200	0.0130	0.0130	0.6804
0.0082	8.1911	40300	0.0128	0.0128	0.6870
0.0082	8.2114	40400	0.0127	0.0127	0.6871
0.0114	8.2317	40500	0.0126	0.0126	0.6900
0.0101	8.2520	40600	0.0129	0.0129	0.6853
0.0099	8.2724	40700	0.0127	0.0127	0.6861
0.0087	8.2927	40800	0.0128	0.0128	0.6850
0.0081	8.3130	40900	0.0127	0.0127	0.6867
0.0086	8.3333	41000	0.0127	0.0127	0.6880
0.0095	8.3537	41100	0.0128	0.0128	0.6867
0.0082	8.3740	41200	0.0128	0.0128	0.6875
0.0075	8.3943	41300	0.0128	0.0128	0.6879
0.0095	8.4146	41400	0.0127	0.0127	0.6882
0.0091	8.4350	41500	0.0127	0.0127	0.6886
0.0098	8.4553	41600	0.0128	0.0128	0.6874
0.0099	8.4756	41700	0.0126	0.0126	0.6907
0.0094	8.4959	41800	0.0129	0.0129	0.6854
0.0097	8.5163	41900	0.0127	0.0127	0.6888
0.0104	8.5366	42000	0.0130	0.0130	0.6856
0.0085	8.5569	42100	0.0129	0.0129	0.6863
0.0083	8.5772	42200	0.0129	0.0129	0.6858
0.0085	8.5976	42300	0.0127	0.0127	0.6897
0.0091	8.6179	42400	0.0127	0.0127	0.6905
0.0092	8.6382	42500	0.0126	0.0126	0.6903
0.0097	8.6585	42600	0.0126	0.0126	0.6901
0.0091	8.6789	42700	0.0127	0.0127	0.6880
0.008	8.6992	42800	0.0128	0.0128	0.6856
0.0093	8.7195	42900	0.0128	0.0128	0.6870
0.0096	8.7398	43000	0.0129	0.0129	0.6853
0.0102	8.7602	43100	0.0126	0.0126	0.6887
0.0097	8.7805	43200	0.0127	0.0127	0.6880
0.0092	8.8008	43300	0.0127	0.0127	0.6885
0.0089	8.8211	43400	0.0128	0.0128	0.6881
0.0083	8.8415	43500	0.0127	0.0127	0.6888
0.0089	8.8618	43600	0.0127	0.0127	0.6887
0.0094	8.8821	43700	0.0127	0.0127	0.6888
0.0085	8.9024	43800	0.0127	0.0127	0.6885
0.0108	8.9228	43900	0.0126	0.0126	0.6907
0.0095	8.9431	44000	0.0127	0.0127	0.6896
0.0082	8.9634	44100	0.0126	0.0126	0.6904
0.0089	8.9837	44200	0.0126	0.0126	0.6913
0.0093	9.0041	44300	0.0126	0.0126	0.6898
0.0091	9.0244	44400	0.0126	0.0126	0.6908
0.0091	9.0447	44500	0.0127	0.0127	0.6896
0.0083	9.0650	44600	0.0126	0.0126	0.6898
0.009	9.0854	44700	0.0126	0.0126	0.6910
0.0097	9.1057	44800	0.0126	0.0126	0.6908
0.0072	9.1260	44900	0.0127	0.0127	0.6877
0.0082	9.1463	45000	0.0127	0.0127	0.6885
0.0078	9.1667	45100	0.0127	0.0127	0.6881
0.0088	9.1870	45200	0.0125	0.0125	0.6914
0.0077	9.2073	45300	0.0127	0.0127	0.6879
0.009	9.2276	45400	0.0126	0.0126	0.6887
0.0088	9.2480	45500	0.0127	0.0127	0.6885
0.0089	9.2683	45600	0.0126	0.0126	0.6915
0.0074	9.2886	45700	0.0126	0.0126	0.6903
0.0085	9.3089	45800	0.0126	0.0126	0.6904
0.0091	9.3293	45900	0.0127	0.0127	0.6892
0.0088	9.3496	46000	0.0125	0.0125	0.6918
0.0094	9.3699	46100	0.0127	0.0127	0.6899
0.0098	9.3902	46200	0.0125	0.0125	0.6931
0.0087	9.4106	46300	0.0126	0.0126	0.6916
0.0086	9.4309	46400	0.0126	0.0126	0.6915
0.0084	9.4512	46500	0.0125	0.0125	0.6931
0.0092	9.4715	46600	0.0126	0.0126	0.6907
0.0087	9.4919	46700	0.0125	0.0125	0.6935
0.0085	9.5122	46800	0.0125	0.0125	0.6938
0.0083	9.5325	46900	0.0125	0.0125	0.6933
0.0091	9.5528	47000	0.0126	0.0126	0.6920
0.0082	9.5732	47100	0.0126	0.0126	0.6912
0.0091	9.5935	47200	0.0126	0.0126	0.6918
0.0092	9.6138	47300	0.0126	0.0126	0.6920
0.0086	9.6341	47400	0.0125	0.0125	0.6930
0.0087	9.6545	47500	0.0125	0.0125	0.6931
0.009	9.6748	47600	0.0126	0.0126	0.6932
0.0085	9.6951	47700	0.0125	0.0125	0.6941
0.0093	9.7154	47800	0.0125	0.0125	0.6930
0.009	9.7358	47900	0.0125	0.0125	0.6930
0.0092	9.7561	48000	0.0125	0.0125	0.6936
0.0093	9.7764	48100	0.0125	0.0125	0.6937
0.0101	9.7967	48200	0.0125	0.0125	0.6935
0.0089	9.8171	48300	0.0125	0.0125	0.6946
0.0087	9.8374	48400	0.0125	0.0125	0.6948
0.008	9.8577	48500	0.0125	0.0125	0.6943
0.0089	9.8780	48600	0.0125	0.0125	0.6944
0.0074	9.8984	48700	0.0125	0.0125	0.6937
0.009	9.9187	48800	0.0125	0.0125	0.6931
0.0077	9.9390	48900	0.0125	0.0125	0.6934
0.0078	9.9593	49000	0.0125	0.0125	0.6937
0.0086	9.9797	49100	0.0125	0.0125	0.6938
0.0074	10.0	49200	0.0125	0.0125	0.6938

Framework versions

Transformers 4.57.3
Pytorch 2.9.1+cu128
Datasets 4.4.2
Tokenizers 0.22.1

Task: Feature Extraction
Library: transformers
Type: stl_encoder
License: mit
Created: Dec 21, 2025
Updated: Dec 24, 2025