This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the YuchenLi01/MATH_Qwen2.5-1.5BInstruct_DPO_MoreUniqueResponseNoGTv2 dataset. It achieves the following results on the evaluation set:

Loss: 0.5067
Rewards/chosen: -1.9118
Rewards/rejected: -3.5562
Rewards/accuracies: 0.7487
Rewards/margins: 1.6444
Logps/rejected: -92.4417
Logps/chosen: -63.6559
Logits/rejected: -2.5758
Logits/chosen: -2.7750

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-07
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Logits/chosen	Logits/rejected	Logps/chosen	Logps/rejected	Validation Loss	Rewards/accuracies	Rewards/chosen	Rewards/margins	Rewards/rejected
0.6995	0.0060	20	-2.2848	-2.1674	-44.5479	-56.8811	0.6936	0.5067	-0.0010	-0.0009	-0.0002
0.695	0.0120	40	-2.2847	-2.1673	-44.5141	-56.8701	0.6936	0.4987	0.0023	0.0014	0.0009
0.6929	0.0180	60	-2.2846	-2.1671	-44.5151	-56.8704	0.6938	0.5267	0.0022	0.0013	0.0009
0.7011	0.0240	80	-2.2866	-2.1689	-44.5270	-56.8827	0.6936	0.5227	0.0011	0.0014	-0.0003
0.6926	0.0300	100	-2.2824	-2.1649	-44.5215	-56.9101	0.6929	0.5428	0.0016	0.0047	-0.0031
0.6894	0.0360	120	-2.2867	-2.1686	-44.5378	-56.8994	0.6928	0.5107	-0.0000	0.0020	-0.0020
0.6855	0.0420	140	-2.2798	-2.1618	-44.5542	-56.9259	0.6926	0.5281	-0.0017	0.0030	-0.0046
0.6913	0.0480	160	-2.2808	-2.1624	-44.5784	-56.9687	0.6916	0.5521	-0.0041	0.0048	-0.0089
0.6833	0.0540	180	-2.2798	-2.1606	-44.5828	-57.0114	0.6899	0.5535	-0.0045	0.0087	-0.0132
0.6949	0.0600	200	-2.2712	-2.1515	-44.6619	-57.1433	0.6881	0.5909	-0.0124	0.0139	-0.0264
0.6881	0.0660	220	-2.2718	-2.1509	-44.7125	-57.2349	0.6860	0.5775	-0.0175	0.0180	-0.0355
0.6829	0.0720	240	-2.2639	-2.1417	-44.8640	-57.4634	0.6828	0.5922	-0.0326	0.0257	-0.0584
0.6898	0.0780	260	-2.2599	-2.1360	-45.0553	-57.7196	0.6802	0.6016	-0.0518	0.0322	-0.0840
0.6656	0.0840	280	-2.2503	-2.1249	-45.2931	-58.0598	0.6759	0.6043	-0.0756	0.0425	-0.1180
0.6682	0.0900	300	-2.2384	-2.1111	-45.5634	-58.4352	0.6713	0.5963	-0.1026	0.0530	-0.1556
0.6703	0.0960	320	-2.2320	-2.1028	-45.7218	-58.7098	0.6670	0.6070	-0.1184	0.0646	-0.1830
0.6571	0.1019	340	-2.2123	-2.0812	-46.1488	-59.3405	0.6606	0.6324	-0.1611	0.0850	-0.2461
0.6382	0.1079	360	-2.1928	-2.0584	-46.6840	-60.1148	0.6528	0.6270	-0.2146	0.1089	-0.3235
0.6032	0.1139	380	-2.1891	-2.0518	-46.9445	-60.6337	0.6450	0.6457	-0.2407	0.1347	-0.3754
0.6068	0.1199	400	-2.1798	-2.0395	-47.2412	-61.1779	0.6372	0.6698	-0.2704	0.1595	-0.4298
0.5947	0.1259	420	-2.1862	-2.0418	-47.6078	-61.9120	0.6279	0.6818	-0.3070	0.1962	-0.5032
0.6137	0.1319	440	-2.1919	-2.0437	-48.0382	-62.6988	0.6197	0.6765	-0.3501	0.2319	-0.5819
0.6256	0.1379	460	-2.1803	-2.0295	-48.6690	-63.6892	0.6111	0.6952	-0.4131	0.2678	-0.6810
0.607	0.1439	480	-2.1940	-2.0392	-49.2011	-64.6990	0.6011	0.6965	-0.4664	0.3156	-0.7819
0.5889	0.1499	500	-2.2080	-2.0491	-49.9403	-65.9371	0.5922	0.7032	-0.5403	0.3655	-0.9058
0.5721	0.1559	520	-2.2320	-2.0689	-50.6720	-67.2714	0.5826	0.7032	-0.6134	0.4257	-1.0392
0.5894	0.1619	540	-2.2568	-2.0905	-51.1458	-68.2701	0.5741	0.7166	-0.6608	0.4782	-1.1391
0.5353	0.1679	560	-2.2574	-2.0895	-51.7675	-69.3926	0.5663	0.7193	-0.7230	0.5283	-1.2513
0.5356	0.1739	580	-2.2933	-2.1236	-52.0209	-69.9965	0.5587	0.7206	-0.7483	0.5634	-1.3117
0.5509	0.1799	600	-2.3180	-2.1467	-52.1855	-70.4398	0.5530	0.7313	-0.7648	0.5912	-1.3560
0.4959	0.1859	620	-2.3457	-2.1708	-52.9189	-71.6958	0.5479	0.7299	-0.8381	0.6435	-1.4816
0.5297	0.1919	640	-2.3834	-2.2065	-53.1923	-72.3656	0.5407	0.7286	-0.8655	0.6831	-1.5486
0.6519	0.1979	660	-2.4054	-2.2272	-53.2749	-72.7275	0.5367	0.7353	-0.8737	0.7111	-1.5848
0.5156	0.2039	680	-2.4421	-2.2627	-53.3589	-73.1044	0.5317	0.7433	-0.8821	0.7404	-1.6225
0.4859	0.2099	700	-2.4735	-2.2924	-53.5985	-73.6654	0.5279	0.7393	-0.9061	0.7725	-1.6786
0.4976	0.2159	720	-2.4884	-2.3073	-53.8496	-74.0923	0.5255	0.7366	-0.9312	0.7901	-1.7213
0.4294	0.2219	740	-2.5181	-2.3363	-54.0775	-74.5767	0.5231	0.7393	-0.9540	0.8157	-1.7697
0.49	0.2279	760	-2.5221	-2.3392	-54.4703	-75.2802	0.5205	0.7420	-0.9933	0.8468	-1.8401
0.5442	0.2339	780	-2.5228	-2.3384	-55.1984	-76.3702	0.5186	0.7380	-1.0661	0.8830	-1.9491
0.5304	0.2399	800	-2.5203	-2.3354	-56.0977	-77.5821	0.5169	0.7366	-1.1560	0.9142	-2.0703
0.5349	0.2459	820	-2.5332	-2.3488	-56.3727	-77.9934	0.5150	0.7393	-1.1835	0.9279	-2.1114
0.5049	0.2519	840	-2.5121	-2.3283	-56.5483	-78.2018	0.5129	0.7313	-1.2011	0.9311	-2.1322
0.5852	0.2579	860	-2.5330	-2.3481	-56.7455	-78.6019	0.5109	0.7299	-1.2208	0.9514	-2.1722
0.4549	0.2639	880	-2.5151	-2.3306	-57.0217	-79.0133	0.5079	0.7393	-1.2484	0.9650	-2.2134
0.5083	0.2699	900	-2.4979	-2.3125	-57.9073	-80.3510	0.5056	0.7353	-1.3370	1.0102	-2.3471
0.5323	0.2759	920	-2.5241	-2.3375	-57.8434	-80.5036	0.5045	0.7380	-1.3306	1.0318	-2.3624
0.5795	0.2819	940	-2.5282	-2.3418	-58.1001	-81.0757	0.5016	0.7380	-1.3563	1.0634	-2.4196
0.5295	0.2879	960	-2.5354	-2.3501	-58.0446	-81.0989	0.5012	0.7340	-1.3507	1.0712	-2.4219
0.5076	0.2939	980	-2.5393	-2.3546	-57.8639	-81.0281	0.4989	0.7366	-1.3326	1.0822	-2.4149
0.4683	0.2999	1000	-2.5524	-2.3660	-57.5254	-80.7145	0.4974	0.7380	-1.2988	1.0847	-2.3835
0.5066	0.3058	1020	-2.5701	-2.3835	-57.6651	-81.0384	0.4978	0.7326	-1.3128	1.1031	-2.4159
0.3888	0.3118	1040	-2.5787	-2.3919	-58.4472	-82.3242	0.4962	0.7406	-1.3910	1.1535	-2.5445
0.3676	0.3178	1060	-2.5895	-2.4013	-58.9905	-83.1713	0.4960	0.7420	-1.4453	1.1839	-2.6292
0.5294	0.3238	1080	-2.5730	-2.3842	-59.7961	-84.3469	0.4971	0.7406	-1.5259	1.2209	-2.7467
0.398	0.3298	1100	-2.5536	-2.3649	-60.7627	-85.7763	0.4983	0.7380	-1.6225	1.2672	-2.8897
0.4169	0.3358	1120	-2.5667	-2.3773	-59.9341	-84.7208	0.4965	0.7353	-1.5397	1.2445	-2.7841
0.457	0.3418	1140	-2.5693	-2.3786	-59.9373	-84.8017	0.4944	0.7406	-1.5400	1.2522	-2.7922
0.3479	0.3478	1160	-2.5839	-2.3916	-60.3877	-85.4529	0.4956	0.7366	-1.5850	1.2723	-2.8573
0.5186	0.3538	1180	-2.5877	-2.3960	-60.1055	-85.2069	0.4939	0.7406	-1.5568	1.2759	-2.8327
0.5129	0.3598	1200	-2.5927	-2.4014	-60.0374	-85.1204	0.4930	0.7406	-1.5500	1.2741	-2.8241
0.3436	0.3658	1220	0.4910	-1.4987	-2.7516	0.75	1.2529	-84.3954	-59.5245	-2.4158	-2.6062
0.5714	0.3718	1240	0.4907	-1.4699	-2.7279	0.7406	1.2580	-84.1581	-59.2365	-2.4230	-2.6142
0.5044	0.3778	1260	0.4905	-1.5038	-2.7698	0.7366	1.2661	-84.5778	-59.5751	-2.4030	-2.5956
0.4815	0.3838	1280	0.4899	-1.5292	-2.8069	0.7326	1.2777	-84.9487	-59.8294	-2.3966	-2.5892
0.3246	0.3898	1300	0.4912	-1.5349	-2.8325	0.7326	1.2977	-85.2050	-59.8865	-2.4146	-2.6069
0.2878	0.3958	1320	0.4933	-1.5806	-2.9077	0.7353	1.3271	-85.9568	-60.3434	-2.4333	-2.6270
0.3344	0.4018	1340	0.4953	-1.6399	-3.0108	0.7420	1.3709	-86.9873	-60.9368	-2.4647	-2.6592
0.3965	0.4078	1360	0.4943	-1.6025	-2.9613	0.7406	1.3588	-86.4927	-60.5622	-2.4575	-2.6521
0.332	0.4138	1380	0.4941	-1.5858	-2.9284	0.7380	1.3426	-86.1632	-60.3954	-2.4551	-2.6496
0.4127	0.4198	1400	0.4942	-1.6682	-3.0640	0.7447	1.3958	-87.5193	-61.2196	-2.4513	-2.6459
0.4837	0.4258	1420	0.4941	-1.6602	-3.0736	0.7473	1.4134	-87.6157	-61.1398	-2.4442	-2.6397
0.5123	0.4318	1440	0.4935	-1.6539	-3.0775	0.7527	1.4236	-87.6547	-61.0765	-2.4426	-2.6387
0.5132	0.4378	1460	0.4942	-1.7107	-3.1495	0.7366	1.4388	-88.3746	-61.6447	-2.4345	-2.6309
0.4641	0.4438	1480	0.4935	-1.6964	-3.1398	0.7433	1.4434	-88.2775	-61.5017	-2.4267	-2.6233
0.4674	0.4498	1500	0.4919	-1.6561	-3.0945	0.7473	1.4384	-87.8242	-61.0984	-2.4310	-2.6277
0.4191	0.4558	1520	0.4919	-1.6363	-3.0849	0.7420	1.4486	-87.7287	-60.9008	-2.4530	-2.6502
0.3379	0.4618	1540	0.4942	-1.6850	-3.1707	0.7473	1.4857	-88.5862	-61.3874	-2.4834	-2.6813
0.3397	0.4678	1560	0.4969	-1.6879	-3.1532	0.7420	1.4653	-88.4119	-61.4168	-2.4984	-2.6963
0.432	0.4738	1580	0.4966	-1.6494	-3.1125	0.7447	1.4632	-88.0047	-61.0311	-2.5167	-2.7143
0.4838	0.4798	1600	0.4972	-1.6685	-3.1215	0.7473	1.4531	-88.0950	-61.2222	-2.5224	-2.7198
0.3043	0.4858	1620	0.4975	-1.7323	-3.2061	0.7447	1.4737	-88.9403	-61.8610	-2.5175	-2.7149
0.3698	0.4918	1640	0.4998	-1.7619	-3.2544	0.7447	1.4925	-89.4236	-62.1568	-2.5154	-2.7129
0.4616	0.4978	1660	0.5016	-1.7244	-3.2080	0.7420	1.4836	-88.9599	-61.7819	-2.5190	-2.7160
0.3774	0.5037	1680	0.5041	-1.7447	-3.2423	0.7433	1.4975	-89.3022	-61.9848	-2.5055	-2.7030
0.473	0.5097	1700	0.5018	-1.7528	-3.2415	0.75	1.4887	-89.2949	-62.0655	-2.4878	-2.6856
0.3644	0.5157	1720	0.4998	-1.7531	-3.2421	0.7473	1.4890	-89.3002	-62.0684	-2.4861	-2.6845
0.3278	0.5217	1740	0.4995	-1.7223	-3.1876	0.7487	1.4653	-88.7556	-61.7604	-2.4735	-2.6716
0.489	0.5277	1760	0.4988	-1.7263	-3.1987	0.7487	1.4724	-88.8661	-61.8004	-2.4788	-2.6766
0.3254	0.5337	1780	0.4963	-1.7185	-3.1829	0.7460	1.4645	-88.7088	-61.7221	-2.4744	-2.6716
0.505	0.5397	1800	0.4977	-1.7532	-3.2521	0.7460	1.4989	-89.4007	-62.0694	-2.4801	-2.6783
0.4589	0.5457	1820	0.4994	-1.7540	-3.2585	0.7433	1.5045	-89.4643	-62.0776	-2.4929	-2.6914
0.3659	0.5517	1840	0.5019	-1.7603	-3.2837	0.7473	1.5234	-89.7162	-62.1402	-2.5294	-2.7276
0.3869	0.5577	1860	0.5004	-1.7361	-3.2445	0.7433	1.5084	-89.3242	-61.8985	-2.5376	-2.7354
0.5639	0.5637	1880	0.5003	-1.7417	-3.2686	0.7473	1.5269	-89.5656	-61.9543	-2.5399	-2.7382
0.3686	0.5697	1900	0.5008	-1.7317	-3.2402	0.7447	1.5085	-89.2817	-61.8549	-2.5302	-2.7285
0.4897	0.5757	1920	0.5002	-1.6936	-3.1971	0.7513	1.5036	-88.8510	-61.4734	-2.5278	-2.7258
0.36	0.5817	1940	0.4988	-1.7331	-3.2547	0.7567	1.5216	-89.4268	-61.8684	-2.5282	-2.7262
0.5182	0.5877	1960	0.5002	-1.7616	-3.2950	0.7540	1.5334	-89.8299	-62.1537	-2.5340	-2.7320
0.4899	0.5937	1980	0.5009	-1.7579	-3.2825	0.7567	1.5246	-89.7042	-62.1166	-2.5346	-2.7325
0.2913	0.5997	2000	0.5003	-1.7057	-3.2005	0.7527	1.4948	-88.8843	-61.5948	-2.5383	-2.7358
0.395	0.6057	2020	0.5009	-1.6974	-3.2026	0.7447	1.5052	-88.9057	-61.5119	-2.5456	-2.7433
0.4316	0.6117	2040	0.5019	-1.7182	-3.2327	0.7553	1.5146	-89.2067	-61.7192	-2.5463	-2.7437
0.4813	0.6177	2060	0.5011	-1.7180	-3.2472	0.7460	1.5293	-89.3517	-61.7171	-2.5597	-2.7577
0.3983	0.6237	2080	0.5018	-1.7300	-3.2559	0.7513	1.5259	-89.4385	-61.8376	-2.5619	-2.7596
0.3464	0.6297	2100	0.5014	-1.7447	-3.2658	0.7527	1.5211	-89.5371	-61.9844	-2.5546	-2.7523
0.429	0.6357	2120	0.5026	-1.7446	-3.2792	0.7527	1.5347	-89.6720	-61.9835	-2.5566	-2.7542
0.4444	0.6417	2140	0.5033	-1.7630	-3.3087	0.7433	1.5457	-89.9661	-62.1672	-2.5544	-2.7519
0.2515	0.6477	2160	0.5031	-1.7579	-3.3035	0.7420	1.5456	-89.9142	-62.1162	-2.5567	-2.7544
0.2195	0.6537	2180	0.5044	-1.8059	-3.3607	0.7553	1.5548	-90.4869	-62.5970	-2.5524	-2.7500
0.4391	0.6597	2200	0.5046	-1.8484	-3.4377	0.7487	1.5893	-91.2566	-63.0220	-2.5563	-2.7544
0.4445	0.6657	2220	0.5039	-1.8158	-3.3836	0.7460	1.5678	-90.7158	-62.6959	-2.5577	-2.7558
0.2732	0.6717	2240	0.5029	-1.7826	-3.3386	0.7487	1.5561	-90.2657	-62.3631	-2.5608	-2.7581
0.3485	0.6777	2260	0.5020	-1.7709	-3.3327	0.7460	1.5618	-90.2064	-62.2462	-2.5646	-2.7618
0.2764	0.6837	2280	0.5027	-1.8077	-3.3758	0.7460	1.5681	-90.6371	-62.6141	-2.5705	-2.7683
0.3255	0.6897	2300	0.5047	-1.8344	-3.4229	0.7487	1.5885	-91.1089	-62.8816	-2.5749	-2.7730
0.3069	0.6957	2320	0.5042	-1.8478	-3.4298	0.7473	1.5820	-91.1778	-63.0155	-2.5683	-2.7662
0.5219	0.7016	2340	0.5043	-1.8394	-3.4301	0.7527	1.5907	-91.1801	-62.9314	-2.5681	-2.7659
0.3437	0.7076	2360	0.5036	-1.8420	-3.4316	0.7460	1.5897	-91.1956	-62.9571	-2.5745	-2.7724
0.3235	0.7136	2380	0.5036	-1.8498	-3.4455	0.7473	1.5957	-91.3341	-63.0351	-2.5745	-2.7726
0.4999	0.7196	2400	0.5036	-1.8553	-3.4464	0.7460	1.5911	-91.3439	-63.0909	-2.5719	-2.7698
0.5426	0.7256	2420	0.5034	-1.8774	-3.4856	0.7447	1.6082	-91.7357	-63.3114	-2.5744	-2.7723
0.4995	0.7316	2440	0.5036	-1.8723	-3.4758	0.7447	1.6036	-91.6377	-63.2601	-2.5747	-2.7729
0.2581	0.7376	2460	0.5029	-1.8503	-3.4534	0.75	1.6031	-91.4139	-63.0409	-2.5798	-2.7779
0.5149	0.7436	2480	0.5040	-1.8462	-3.4402	0.7473	1.5941	-91.2820	-62.9991	-2.5816	-2.7801
0.6443	0.7496	2500	0.5041	-1.8477	-3.4363	0.7473	1.5886	-91.2422	-63.0145	-2.5772	-2.7755
0.328	0.7556	2520	0.5035	-1.8616	-3.4542	0.7487	1.5926	-91.4215	-63.1539	-2.5642	-2.7625
0.3677	0.7616	2540	0.5043	-1.8738	-3.4654	0.7433	1.5916	-91.5333	-63.2752	-2.5710	-2.7697
0.4308	0.7676	2560	0.5045	-1.8730	-3.4766	0.7460	1.6036	-91.6454	-63.2678	-2.5717	-2.7706
0.3779	0.7736	2580	0.5045	-1.8738	-3.4806	0.7527	1.6068	-91.6860	-63.2759	-2.5697	-2.7685
0.252	0.7796	2600	0.5054	-1.8748	-3.4775	0.7460	1.6027	-91.6550	-63.2858	-2.5721	-2.7709
0.4459	0.7856	2620	0.5045	-1.8707	-3.4790	0.7527	1.6083	-91.6696	-63.2450	-2.5676	-2.7662
0.424	0.7916	2640	0.5049	-1.8814	-3.4951	0.7447	1.6137	-91.8306	-63.3511	-2.5752	-2.7741
0.2953	0.7976	2660	0.5050	-1.8849	-3.5023	0.7540	1.6174	-91.9023	-63.3867	-2.5697	-2.7688
0.3491	0.8036	2680	0.5054	-1.8880	-3.5089	0.7460	1.6209	-91.9688	-63.4174	-2.5772	-2.7764
0.3599	0.8096	2700	0.5065	-1.8902	-3.5118	0.7460	1.6217	-91.9976	-63.4391	-2.5745	-2.7733
0.386	0.8156	2720	0.5062	-1.8956	-3.5192	0.7473	1.6236	-92.0715	-63.4934	-2.5782	-2.7772
0.4701	0.8216	2740	0.5065	-1.8962	-3.5213	0.7513	1.6251	-92.0922	-63.4997	-2.5731	-2.7721
0.2747	0.8276	2760	0.5067	-1.9011	-3.5252	0.7513	1.6241	-92.1316	-63.5485	-2.5746	-2.7734
0.5562	0.8336	2780	0.5058	-1.9007	-3.5290	0.7420	1.6283	-92.1700	-63.5447	-2.5773	-2.7762
0.3504	0.8396	2800	0.5056	-1.8947	-3.5166	0.7487	1.6219	-92.0454	-63.4845	-2.5710	-2.7701
0.3125	0.8456	2820	0.5052	-1.8942	-3.5245	0.7527	1.6304	-92.1250	-63.4793	-2.5717	-2.7712
0.2564	0.8516	2840	0.5054	-1.8956	-3.5211	0.75	1.6255	-92.0910	-63.4936	-2.5735	-2.7728
0.4186	0.8576	2860	0.5063	-1.9014	-3.5334	0.7473	1.6319	-92.2131	-63.5517	-2.5768	-2.7762
0.3605	0.8636	2880	0.5061	-1.9002	-3.5389	0.7513	1.6387	-92.2684	-63.5396	-2.5758	-2.7750
0.308	0.8696	2900	0.5069	-1.9033	-3.5368	0.7473	1.6335	-92.2473	-63.5705	-2.5761	-2.7753
0.351	0.8756	2920	0.5061	-1.9006	-3.5409	0.7527	1.6403	-92.2885	-63.5435	-2.5774	-2.7767
0.3014	0.8816	2940	0.5062	-1.9033	-3.5465	0.7513	1.6432	-92.3441	-63.5702	-2.5780	-2.7774
0.3245	0.8876	2960	0.5066	-1.9096	-3.5536	0.7527	1.6439	-92.4150	-63.6339	-2.5765	-2.7758
0.4174	0.8936	2980	0.5058	-1.9135	-3.5567	0.7460	1.6432	-92.4464	-63.6725	-2.5732	-2.7724
0.3974	0.8996	3000	0.5060	-1.9121	-3.5536	0.7460	1.6415	-92.4155	-63.6582	-2.5761	-2.7754
0.4164	0.9055	3020	0.5066	-1.9177	-3.5587	0.7487	1.6410	-92.4665	-63.7149	-2.5771	-2.7763
0.4347	0.9115	3040	0.5068	-1.9116	-3.5647	0.7460	1.6532	-92.5270	-63.6535	-2.5719	-2.7709
0.3585	0.9175	3060	0.5063	-1.9124	-3.5601	0.7513	1.6476	-92.4803	-63.6620	-2.5766	-2.7760
0.2751	0.9235	3080	0.5069	-1.9171	-3.5629	0.7460	1.6458	-92.5086	-63.7086	-2.5738	-2.7730
0.3814	0.9295	3100	0.5067	-1.9137	-3.5568	0.7473	1.6431	-92.4477	-63.6746	-2.5743	-2.7737
0.2938	0.9355	3120	0.5078	-1.9183	-3.5577	0.7433	1.6394	-92.4567	-63.7204	-2.5738	-2.7730
0.3139	0.9415	3140	0.5066	-1.9126	-3.5573	0.7487	1.6447	-92.4528	-63.6640	-2.5768	-2.7761
0.2736	0.9475	3160	0.5055	-1.9117	-3.5558	0.7433	1.6442	-92.4377	-63.6541	-2.5791	-2.7785
0.337	0.9535	3180	0.5054	-1.9127	-3.5533	0.7487	1.6406	-92.4127	-63.6642	-2.5785	-2.7783
0.4195	0.9595	3200	0.5065	-1.9143	-3.5562	0.7567	1.6419	-92.4415	-63.6808	-2.5750	-2.7743
0.217	0.9655	3220	0.5078	-1.9156	-3.5579	0.7553	1.6422	-92.4582	-63.6938	-2.5763	-2.7758
0.3457	0.9715	3240	0.5069	-1.9132	-3.5567	0.7527	1.6435	-92.4466	-63.6700	-2.5734	-2.7728
0.3972	0.9775	3260	0.5069	-1.9102	-3.5582	0.7527	1.6480	-92.4614	-63.6394	-2.5780	-2.7771
0.2465	0.9835	3280	0.5070	-1.9089	-3.5582	0.7460	1.6493	-92.4619	-63.6270	-2.5751	-2.7744
0.4011	0.9895	3300	0.5067	-1.9112	-3.5581	0.7487	1.6469	-92.4605	-63.6494	-2.5769	-2.7764
0.4849	0.9955	3320	0.5074	-1.9135	-3.5596	0.7460	1.6460	-92.4754	-63.6730	-2.5759	-2.7752

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+cu121
Datasets 3.5.0
Tokenizers 0.20.3

YuchenLi01/generatedMoreUniqueResponseNoGTv2_Qwen2.5-1.5BInstruct_dpo_ebs32_lr5e-07_beta0.1_42

generatedMoreUniqueResponseNoGTv2_Qwen2.5-1.5BInstruct_dpo_ebs32_lr5e-07_beta0.1_42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

YuchenLi01/
generatedMoreUniqueResponseNoGTv2_Qwen2.5-1.5BInstruct_dpo_ebs32_lr5e-07_beta0.1_42