learning_rate: 0.0001
train_batch_size: 1
eval_batch_size: 1
seed: 12345
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 8
total_eval_batch_size: 8
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Roc Auc	Best Threshold	Tpr At Best Threshold	Fpr At Best Threshold	Accuracy At Best Threshold	Avg Score True Positives	Avg Score True Negatives
No log	0	0	40.8364	0.6060	0.0100	0.4225	0.1364	0.5269	0.1403	0.0493
30.0264	0.0820	5	40.4295	0.6042	0.0110	0.4296	0.1591	0.5269	0.1427	0.0520
11.206	0.1639	10	39.1235	0.6047	0.0199	0.4014	0.1364	0.5108	0.1528	0.0545
24.0257	0.2459	15	36.3912	0.6079	0.0107	0.4789	0.2045	0.5538	0.1762	0.0621
33.373	0.3279	20	30.3600	0.6162	0.0588	0.4507	0.1591	0.5430	0.2450	0.0801
7.6036	0.4098	25	21.2878	0.6204	0.6637	0.3451	0.0682	0.4839	0.3934	0.1809
4.8281	0.4918	30	17.2191	0.6208	0.8007	0.4085	0.1136	0.5215	0.4993	0.3014
20.1162	0.5738	35	13.4890	0.6378	0.9320	0.4789	0.0909	0.5806	0.6033	0.4540
22.4787	0.6557	40	11.8872	0.6478	0.9566	0.5070	0.1364	0.5914	0.6576	0.5302
25.7205	0.7377	45	11.6109	0.6454	0.9515	0.4859	0.1364	0.5753	0.6521	0.5361
10.3629	0.8197	50	13.4303	0.6500	0.7753	0.4859	0.1136	0.5806	0.5384	0.3201
13.459	0.9016	55	12.9827	0.6555	0.8719	0.3662	0.0455	0.5054	0.5175	0.2831
17.2672	0.9836	60	11.2697	0.6658	0.9089	0.3310	0.0455	0.4785	0.5208	0.2937
0.5007	1.0656	65	6.8518	0.6580	0.9881	0.3873	0.0909	0.5108	0.7785	0.6468
20.4504	1.1475	70	6.8325	0.6515	0.9669	0.4437	0.1364	0.5430	0.7569	0.6404
28.2775	1.2295	75	8.0759	0.6576	0.5889	0.5915	0.2727	0.6237	0.6083	0.4236
4.8831	1.3115	80	9.2844	0.6855	0.8267	0.4085	0.0909	0.5269	0.5575	0.3262
4.672	1.3934	85	7.4915	0.6985	0.9230	0.4225	0.0909	0.5376	0.6700	0.4517
15.8043	1.4754	90	7.0059	0.7279	0.7991	0.6197	0.1591	0.6720	0.7172	0.4677
20.7102	1.5574	95	9.8493	0.7292	0.3522	0.6408	0.1818	0.6828	0.5505	0.2327
9.2205	1.6393	100	9.8750	0.7396	0.5273	0.5563	0.1364	0.6290	0.5568	0.2283
5.812	1.7213	105	9.0059	0.7430	0.4073	0.6901	0.25	0.7043	0.6034	0.2794
3.3269	1.8033	110	7.8423	0.7334	0.9112	0.4789	0.0682	0.5860	0.6814	0.4044
6.9746	1.8852	115	10.0511	0.7258	0.2583	0.6831	0.25	0.6989	0.5477	0.2378
2.7945	1.9672	120	8.8034	0.7393	0.3812	0.6831	0.2273	0.7043	0.5976	0.2663
3.8485	2.0492	125	7.3595	0.7382	0.6487	0.6408	0.1818	0.6828	0.6686	0.3525
1.7471	2.1311	130	10.0556	0.7505	0.2261	0.6549	0.1591	0.6989	0.5124	0.1923
5.4654	2.2131	135	6.9356	0.7506	0.7680	0.6268	0.1591	0.6774	0.7217	0.4046
13.8093	2.2951	140	7.0183	0.7585	0.9858	0.6408	0.1591	0.6882	0.8865	0.7057
2.5921	2.3770	145	6.7241	0.7606	0.7351	0.7324	0.25	0.7366	0.7662	0.4377
2.8333	2.4590	150	17.9904	0.7514	0.0204	0.7113	0.2727	0.7151	0.2735	0.0705
11.9122	2.5410	155	11.5724	0.7518	0.1192	0.7113	0.2273	0.7258	0.4622	0.1639
0.6597	2.6230	160	7.2389	0.7599	0.9763	0.7324	0.25	0.7366	0.8903	0.7144
20.6605	2.7049	165	9.3035	0.7490	0.9974	0.6761	0.2273	0.6989	0.9340	0.8161
3.7395	2.7869	170	7.0056	0.7482	0.8155	0.6901	0.25	0.7043	0.7679	0.4520
1.7925	2.8689	175	10.8332	0.7546	0.4927	0.5775	0.1136	0.6505	0.5349	0.1926
7.7368	2.9508	180	8.3963	0.7654	0.3720	0.7394	0.2727	0.7366	0.6530	0.2603
0.7472	3.0328	185	7.6301	0.7658	0.6826	0.6761	0.2045	0.7043	0.7171	0.3162
0.2008	3.1148	190	7.5858	0.7689	0.5293	0.7676	0.2727	0.7581	0.7337	0.3239
11.3118	3.1967	195	7.8013	0.7700	0.6783	0.6831	0.2045	0.7097	0.7143	0.3056
2.8929	3.2787	200	7.1610	0.7682	0.8454	0.7183	0.2273	0.7312	0.7899	0.4090
0.0448	3.3607	205	7.5174	0.7643	0.7953	0.7394	0.25	0.7419	0.7703	0.3865
1.7686	3.4426	210	7.1019	0.7611	0.7827	0.7606	0.2727	0.7527	0.8140	0.4608
0.6789	3.5246	215	7.3242	0.7701	0.9468	0.7887	0.2955	0.7688	0.8903	0.5851
9.9854	3.6066	220	8.5934	0.7805	0.9904	0.7887	0.2955	0.7688	0.9317	0.6784
0.9469	3.6885	225	6.7015	0.7946	0.4581	0.7746	0.2727	0.7634	0.7507	0.3372
0.562	3.7705	230	7.2274	0.7910	0.5278	0.7113	0.2273	0.7258	0.6863	0.2900
0.1441	3.8525	235	5.9444	0.7902	0.8860	0.6761	0.1818	0.7097	0.8094	0.4582
0.1231	3.9344	240	7.2327	0.7754	0.9913	0.6972	0.2045	0.7204	0.9131	0.6519
7.5397	4.0164	245	7.9786	0.7790	0.9952	0.7113	0.2045	0.7312	0.9305	0.6903
0.9936	4.0984	250	7.6964	0.7758	0.9919	0.7113	0.1818	0.7366	0.9132	0.6416
0.031	4.1803	255	6.7873	0.7713	0.9412	0.6620	0.1818	0.6989	0.8261	0.4891
0.0097	4.2623	260	7.4284	0.7631	0.9889	0.6408	0.1818	0.6828	0.8772	0.5659
0.4529	4.3443	265	14.3212	0.7664	1.0000	0.6268	0.1818	0.6720	0.9685	0.8226
0.6865	4.4262	270	12.4413	0.7749	0.9999	0.6549	0.1818	0.6935	0.9597	0.7794
0.0345	4.5082	275	7.3264	0.7905	0.9621	0.7535	0.2273	0.7581	0.8858	0.5221
0.0155	4.5902	280	7.9462	0.7847	0.6393	0.7746	0.2727	0.7634	0.7752	0.3378
0.0053	4.6721	285	9.0044	0.7847	0.9804	0.8451	0.3409	0.8011	0.9260	0.5891
0.0187	4.7541	290	13.4543	0.7716	0.9998	0.8099	0.3409	0.7742	0.9705	0.7615
0.3543	4.8361	295	14.5769	0.7580	1.0000	0.6901	0.25	0.7043	0.9750	0.7810
0.1773	4.9180	300	10.7964	0.7697	0.9980	0.7887	0.3182	0.7634	0.9465	0.6736
4.4075	5.0	305	9.1733	0.7730	0.9945	0.7324	0.2727	0.7312	0.9198	0.5895
0.0002	5.0820	310	9.9484	0.7677	0.9956	0.7817	0.3182	0.7581	0.9305	0.6290
0.0004	5.1639	315	10.7925	0.7641	0.9986	0.7465	0.2955	0.7366	0.9399	0.6685
0.0388	5.2459	320	14.3326	0.7575	0.9999	0.7113	0.2727	0.7151	0.9619	0.7779
0.0085	5.3279	325	14.3211	0.7505	0.9999	0.7254	0.3182	0.7151	0.9638	0.7731
0.0016	5.4098	330	14.3540	0.7544	0.9999	0.7676	0.3182	0.7473	0.9606	0.7739
0.0198	5.4918	335	15.7319	0.7517	1.0000	0.7324	0.2727	0.7312	0.9706	0.8039
0.0001	5.5738	340	16.4489	0.7550	1.0000	0.8028	0.3864	0.7581	0.9699	0.8153
0.0002	5.6557	345	15.4570	0.7610	1.0000	0.7535	0.2727	0.7473	0.9643	0.7916
0.0003	5.7377	350	12.9847	0.7686	0.9999	0.6901	0.25	0.7043	0.9520	0.7087
0.001	5.8197	355	13.3568	0.7606	0.9997	0.7887	0.3182	0.7634	0.9509	0.7175
1.8059	5.9016	360	15.2187	0.7598	1.0000	0.7394	0.2727	0.7366	0.9634	0.7689
0.0034	5.9836	365	16.7669	0.7577	1.0000	0.8169	0.3636	0.7742	0.9665	0.8080
0.5196	6.0656	370	16.1938	0.7601	1.0000	0.7887	0.3182	0.7634	0.9664	0.7935
0.0002	6.1475	375	16.6469	0.7594	1.0000	0.7465	0.2727	0.7419	0.9683	0.8171
0.0005	6.2295	380	16.6037	0.7639	1.0000	0.7746	0.2955	0.7581	0.9670	0.8078
0.0007	6.3115	385	15.8511	0.7618	0.9999	0.7746	0.3182	0.7527	0.9638	0.7922
0.0002	6.3934	390	14.8609	0.7602	0.9999	0.7676	0.2955	0.7527	0.9604	0.7553
0.0	6.4754	395	14.3824	0.7646	0.9998	0.7958	0.3409	0.7634	0.9577	0.7504
0.0	6.5574	400	14.7481	0.7656	0.9999	0.7887	0.3409	0.7581	0.9597	0.7560
0.0	6.6393	405	15.0264	0.7641	1.0000	0.7042	0.25	0.7151	0.9609	0.7630
0.0068	6.7213	410	15.1765	0.7662	1.0000	0.7394	0.2727	0.7366	0.9609	0.7677
0.598	6.8033	415	16.1313	0.7662	1.0000	0.7465	0.2727	0.7419	0.9642	0.7771
0.0021	6.8852	420	17.4269	0.7610	1.0000	0.7535	0.2955	0.7419	0.9698	0.8189
0.0	6.9672	425	17.6265	0.7556	1.0000	0.6901	0.25	0.7043	0.9708	0.8062
0.0	7.0492	430	18.0737	0.7493	1.0000	0.7113	0.2727	0.7151	0.9703	0.8268
0.0	7.1311	435	17.9544	0.7430	1.0000	0.6690	0.25	0.6882	0.9686	0.8188
0.0002	7.2131	440	17.7111	0.7511	1.0000	0.6831	0.25	0.6989	0.9686	0.8139
0.0	7.2951	445	17.5092	0.7446	1.0000	0.7042	0.2727	0.7097	0.9669	0.8038
0.0005	7.3770	450	17.3533	0.7481	1.0000	0.7183	0.2727	0.7204	0.9697	0.8029
0.0003	7.4590	455	17.6086	0.7493	1.0000	0.7113	0.2727	0.7151	0.9698	0.8209
0.0001	7.5410	460	18.8623	0.7395	1.0000	0.6831	0.25	0.6989	0.9730	0.8307
0.0	7.6230	465	19.4190	0.7268	1.0000	0.6620	0.25	0.6828	0.9763	0.8409
0.0	7.7049	470	18.8594	0.7221	1.0000	0.6690	0.25	0.6882	0.9747	0.8352
0.0003	7.7869	475	18.2645	0.7410	1.0000	0.7042	0.2727	0.7097	0.9725	0.8281
0.0	7.8689	480	18.1157	0.7471	1.0000	0.6761	0.25	0.6935	0.9709	0.8227
0.0	7.9508	485	18.1191	0.7432	1.0000	0.6831	0.25	0.6989	0.9705	0.8242
0.0	8.0328	490	17.7896	0.7383	1.0000	0.6901	0.25	0.7043	0.9703	0.8148
0.0	8.1148	495	17.8556	0.7378	1.0000	0.6620	0.25	0.6828	0.9725	0.8151
0.0001	8.1967	500	18.4986	0.7181	1.0000	0.6620	0.2727	0.6774	0.9712	0.8315
0.0001	8.2787	505	18.5772	0.7244	1.0000	0.6479	0.25	0.6720	0.9729	0.8314
0.0397	8.3607	510	18.4962	0.7278	1.0000	0.6901	0.2955	0.6935	0.9713	0.8226
0.0004	8.4426	515	18.6584	0.7378	1.0000	0.6831	0.25	0.6989	0.9722	0.8319
0.0002	8.5246	520	18.5779	0.7304	1.0000	0.6620	0.25	0.6828	0.9718	0.8295
0.0001	8.6066	525	18.7075	0.7230	1.0000	0.7324	0.3182	0.7204	0.9734	0.8273
0.0	8.6885	530	18.4215	0.7262	1.0000	0.7394	0.3182	0.7258	0.9708	0.8201
0.0	8.7705	535	18.3408	0.7240	1.0000	0.6690	0.25	0.6882	0.9724	0.8135
0.0001	8.8525	540	18.5811	0.7230	1.0000	0.6620	0.2727	0.6774	0.9721	0.8343
0.0	8.9344	545	18.3932	0.7327	1.0000	0.7042	0.2727	0.7097	0.9741	0.8247
0.0002	9.0164	550	18.3769	0.7397	1.0000	0.6901	0.2727	0.6989	0.9709	0.8309
0.0	9.0984	555	18.5722	0.7344	1.0000	0.6549	0.25	0.6774	0.9715	0.8212
0.0002	9.1803	560	18.7028	0.7293	1.0000	0.6761	0.25	0.6935	0.9715	0.8313
0.0001	9.2623	565	18.6149	0.7312	1.0000	0.6620	0.25	0.6828	0.9751	0.8226
0.0	9.3443	570	18.4985	0.7277	1.0000	0.6479	0.2727	0.6667	0.9711	0.8228
0.0	9.4262	575	18.5147	0.7302	1.0000	0.7394	0.3409	0.7204	0.9734	0.8258
0.0002	9.5082	580	18.5531	0.7401	1.0000	0.7113	0.2955	0.7097	0.9733	0.8281
0.0	9.5902	585	18.5682	0.7259	1.0000	0.6761	0.25	0.6935	0.9715	0.8168
0.0008	9.6721	590	18.5335	0.7337	1.0000	0.6268	0.25	0.6559	0.9724	0.8238
0.0	9.7541	595	18.4988	0.7377	1.0000	0.6690	0.25	0.6882	0.9709	0.8265
0.0047	9.8361	600	18.6238	0.7305	1.0000	0.6549	0.25	0.6774	0.9722	0.8282
0.0	9.9180	605	18.6374	0.7291	1.0000	0.6690	0.25	0.6882	0.9759	0.8279
0.0	10.0	610	18.3850	0.7289	1.0000	0.7324	0.2955	0.7258	0.9721	0.8292

Framework versions

PEFT 0.18.1
Transformers 4.57.6
Pytorch 2.9.1+cu128
Datasets 4.5.0
Tokenizers 0.22.2

leobianco/bosch_RM_Qwen_S12345_LLM_false_STRUCT_true_epo10_lr1e-4_r8_2602041440

bosch_RM_Qwen_S12345_LLM_false_STRUCT_true_epo10_lr1e-4_r8_2602041440

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

leobianco/
bosch_RM_Qwen_S12345_LLM_false_STRUCT_true_epo10_lr1e-4_r8_2602041440