learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 112
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.001
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Mdl	Accumulated Loss	Correct Preds	Total Preds	Accuracy	Correct Gen Preds	Gen Accuracy	Correct Gen Preds 32	Correct Preds 32	Total Labels 32	Accuracy 32	Gen Accuracy 32	Correct Gen Preds 33	Correct Preds 33	Total Labels 33	Accuracy 33	Gen Accuracy 33	Correct Gen Preds 34	Correct Preds 34	Total Labels 34	Accuracy 34	Gen Accuracy 34	Correct Gen Preds 35	Correct Preds 35	Total Labels 35	Accuracy 35	Gen Accuracy 35	Total Labels 36
No log	0	0	1.6389	0.0059	706.9523	490.0220	66.0	299.0	0.2207	66.0	0.2207	62.0	62.0	64.0	0.9688	0.9688	0.0	0.0	73.0	0.0	0.0	4.0	4.0	78.0	0.0513	0.0513	0.0	0.0	83.0	0.0	0.0	1.0
1.8654	1.0	1	2.2664	0.0059	977.6436	677.6509	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
1.4169	2.0	2	1.5070	0.0059	650.0659	450.5913	85.0	299.0	0.2843	85.0	0.2843	0.0	0.0	64.0	0.0	0.0	4.0	4.0	73.0	0.0548	0.0548	1.0	1.0	78.0	0.0128	0.0128	80.0	80.0	83.0	0.9639	0.9639	1.0
0.8781	3.0	3	1.8141	0.0059	782.5587	542.4284	78.0	299.0	0.2609	62.0	0.2074	2.0	5.0	64.0	0.0781	0.0312	54.0	65.0	73.0	0.8904	0.7397	5.0	6.0	78.0	0.0769	0.0641	1.0	2.0	83.0	0.0241	0.0120	1.0
0.188	4.0	4	2.8015	0.0059	1208.4777	837.6529	81.0	299.0	0.2709	61.0	0.2040	0.0	1.0	64.0	0.0156	0.0	42.0	57.0	73.0	0.7808	0.5753	17.0	18.0	78.0	0.2308	0.2179	2.0	5.0	83.0	0.0602	0.0241	1.0
0.0029	5.0	5	4.8971	0.0059	2112.4219	1464.2193	84.0	299.0	0.2809	54.0	0.1806	0.0	0.0	64.0	0.0	0.0	26.0	47.0	73.0	0.6438	0.3562	23.0	28.0	78.0	0.3590	0.2949	5.0	9.0	83.0	0.1084	0.0602	1.0
0.0	6.0	6	6.1245	0.0059	2641.8949	1831.2220	97.0	299.0	0.3244	68.0	0.2274	0.0	0.0	64.0	0.0	0.0	25.0	45.0	73.0	0.6164	0.3425	38.0	43.0	78.0	0.5513	0.4872	5.0	9.0	83.0	0.1084	0.0602	1.0
0.0	7.0	7	6.7643	0.0059	2917.8804	2022.5206	99.0	299.0	0.3311	69.0	0.2308	0.0	0.0	64.0	0.0	0.0	22.0	41.0	73.0	0.5616	0.3014	36.0	43.0	78.0	0.5513	0.4615	11.0	15.0	83.0	0.1807	0.1325	1.0
0.0	8.0	8	7.2082	0.0059	3109.3531	2155.2393	103.0	299.0	0.3445	78.0	0.2609	0.0	0.0	64.0	0.0	0.0	21.0	36.0	73.0	0.4932	0.2877	43.0	48.0	78.0	0.6154	0.5513	14.0	19.0	83.0	0.2289	0.1687	1.0
0.0	9.0	9	7.4224	0.0059	3201.7859	2219.3088	102.0	299.0	0.3411	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	20.0	33.0	73.0	0.4521	0.2740	42.0	49.0	78.0	0.6282	0.5385	14.0	20.0	83.0	0.2410	0.1687	1.0
0.0	10.0	10	7.5258	0.0059	3246.3641	2250.2081	103.0	299.0	0.3445	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	19.0	29.0	73.0	0.3973	0.2603	42.0	49.0	78.0	0.6282	0.5385	16.0	25.0	83.0	0.3012	0.1928	1.0
0.0	11.0	11	7.5992	0.0059	3278.0554	2272.1749	103.0	299.0	0.3445	78.0	0.2609	0.0	0.0	64.0	0.0	0.0	18.0	29.0	73.0	0.3973	0.2466	43.0	48.0	78.0	0.6154	0.5513	17.0	26.0	83.0	0.3133	0.2048	1.0
0.0	12.0	12	7.6533	0.0059	3301.3600	2288.3284	105.0	299.0	0.3512	79.0	0.2642	0.0	0.0	64.0	0.0	0.0	19.0	29.0	73.0	0.3973	0.2603	42.0	48.0	78.0	0.6154	0.5385	18.0	28.0	83.0	0.3373	0.2169	1.0
0.0	13.0	13	7.6654	0.0059	3306.5761	2291.9439	105.0	299.0	0.3512	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	17.0	28.0	73.0	0.3836	0.2329	42.0	48.0	78.0	0.6154	0.5385	18.0	29.0	83.0	0.3494	0.2169	1.0
0.0	14.0	14	7.6672	0.0059	3307.3703	2292.4944	103.0	299.0	0.3445	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	14.0	24.0	73.0	0.3288	0.1918	42.0	48.0	78.0	0.6154	0.5385	20.0	31.0	83.0	0.3735	0.2410	1.0
0.0	15.0	15	7.6055	0.0059	3280.7549	2274.0460	104.0	299.0	0.3478	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	12.0	23.0	73.0	0.3151	0.1644	42.0	48.0	78.0	0.6154	0.5385	22.0	33.0	83.0	0.3976	0.2651	1.0
0.0	16.0	16	7.6060	0.0059	3280.9758	2274.1991	103.0	299.0	0.3445	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	11.0	22.0	73.0	0.3014	0.1507	42.0	48.0	78.0	0.6154	0.5385	22.0	33.0	83.0	0.3976	0.2651	1.0
0.0	17.0	17	7.6496	0.0059	3299.7930	2287.2422	101.0	299.0	0.3378	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	20.0	73.0	0.2740	0.1370	42.0	48.0	78.0	0.6154	0.5385	23.0	33.0	83.0	0.3976	0.2771	1.0
0.0	18.0	18	7.6913	0.0059	3317.7443	2299.6851	100.0	299.0	0.3344	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	19.0	73.0	0.2603	0.1370	42.0	48.0	78.0	0.6154	0.5385	24.0	33.0	83.0	0.3976	0.2892	1.0
0.0	19.0	19	7.6402	0.0059	3295.7208	2284.4196	99.0	299.0	0.3311	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	10.0	19.0	73.0	0.2603	0.1370	40.0	47.0	78.0	0.6026	0.5128	23.0	33.0	83.0	0.3976	0.2771	1.0
0.0	20.0	20	7.6459	0.0059	3298.1814	2286.1251	101.0	299.0	0.3378	74.0	0.2475	0.0	0.0	64.0	0.0	0.0	10.0	20.0	73.0	0.2740	0.1370	41.0	47.0	78.0	0.6026	0.5256	23.0	34.0	83.0	0.4096	0.2771	1.0
0.0	21.0	21	7.6967	0.0059	3320.0870	2301.3090	99.0	299.0	0.3311	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	11.0	19.0	73.0	0.2603	0.1507	40.0	47.0	78.0	0.6026	0.5128	24.0	33.0	83.0	0.3976	0.2892	1.0
0.0	22.0	22	7.7387	0.0059	3338.2217	2313.8790	99.0	299.0	0.3311	74.0	0.2475	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	40.0	47.0	78.0	0.6026	0.5128	24.0	34.0	83.0	0.4096	0.2892	1.0
0.0	23.0	23	7.6979	0.0059	3320.6145	2301.6746	101.0	299.0	0.3378	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	19.0	73.0	0.2603	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	35.0	83.0	0.4217	0.3133	1.0
0.0	24.0	24	7.6949	0.0059	3319.3001	2300.7635	101.0	299.0	0.3378	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	40.0	47.0	78.0	0.6026	0.5128	25.0	36.0	83.0	0.4337	0.3012	1.0
0.0	25.0	25	7.7195	0.0059	3329.9467	2308.1432	104.0	299.0	0.3478	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	19.0	73.0	0.2603	0.1370	41.0	48.0	78.0	0.6154	0.5256	25.0	37.0	83.0	0.4458	0.3012	1.0
0.0	26.0	26	7.7448	0.0059	3340.8562	2315.7051	101.0	299.0	0.3378	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	40.0	47.0	78.0	0.6026	0.5128	25.0	36.0	83.0	0.4337	0.3012	1.0
0.0	27.0	27	7.7632	0.0059	3348.7873	2321.2025	99.0	299.0	0.3311	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	11.0	17.0	73.0	0.2329	0.1507	40.0	47.0	78.0	0.6026	0.5128	25.0	35.0	83.0	0.4217	0.3012	1.0
0.0	28.0	28	7.7346	0.0059	3336.4246	2312.6333	100.0	299.0	0.3344	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	36.0	83.0	0.4337	0.3133	1.0
0.0	29.0	29	7.7372	0.0059	3337.5522	2313.4149	101.0	299.0	0.3378	78.0	0.2609	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	28.0	37.0	83.0	0.4458	0.3373	1.0
0.0	30.0	30	7.7743	0.0059	3353.5641	2324.5135	102.0	299.0	0.3411	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	31.0	31	7.7349	0.0059	3336.5601	2312.7272	101.0	299.0	0.3378	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	36.0	83.0	0.4337	0.3133	1.0
0.0	32.0	32	7.7546	0.0059	3345.0551	2318.6155	102.0	299.0	0.3411	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	11.0	18.0	73.0	0.2466	0.1507	40.0	47.0	78.0	0.6026	0.5128	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	33.0	33	7.7929	0.0059	3361.6005	2330.0839	101.0	299.0	0.3378	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	34.0	34	7.7482	0.0059	3342.3069	2316.7106	102.0	299.0	0.3411	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	41.0	48.0	78.0	0.6154	0.5256	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	35.0	35	7.8004	0.0059	3364.8058	2332.3057	101.0	299.0	0.3378	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	11.0	17.0	73.0	0.2329	0.1507	40.0	47.0	78.0	0.6026	0.5128	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	36.0	36	7.7427	0.0059	3339.9320	2315.0645	101.0	299.0	0.3378	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	39.0	47.0	78.0	0.6026	0.5	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	37.0	37	7.8061	0.0059	3367.2820	2334.0220	99.0	299.0	0.3311	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	16.0	73.0	0.2192	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	36.0	83.0	0.4337	0.3133	1.0
0.0	38.0	38	7.8022	0.0059	3365.5881	2332.8479	99.0	299.0	0.3311	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	16.0	73.0	0.2192	0.1370	40.0	47.0	78.0	0.6026	0.5128	25.0	36.0	83.0	0.4337	0.3012	1.0
0.0	39.0	39	7.7947	0.0059	3362.3815	2330.6252	100.0	299.0	0.3344	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	36.0	83.0	0.4337	0.3133	1.0
0.0	40.0	40	7.7940	0.0059	3362.0791	2330.4156	101.0	299.0	0.3378	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	41.0	41	7.7956	0.0059	3362.7762	2330.8989	100.0	299.0	0.3344	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	36.0	83.0	0.4337	0.3133	1.0
0.0	42.0	42	7.8046	0.0059	3366.6325	2333.5718	97.0	299.0	0.3244	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	11.0	16.0	73.0	0.2192	0.1507	40.0	47.0	78.0	0.6026	0.5128	24.0	34.0	83.0	0.4096	0.2892	1.0
0.0	43.0	43	7.7742	0.0059	3353.5392	2324.4962	102.0	299.0	0.3411	78.0	0.2609	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	41.0	48.0	78.0	0.6154	0.5256	27.0	37.0	83.0	0.4458	0.3253	1.0
0.0	44.0	44	7.7996	0.0059	3364.4841	2332.0826	100.0	299.0	0.3344	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	25.0	36.0	83.0	0.4337	0.3012	1.0
0.0	45.0	45	7.7782	0.0059	3355.2556	2325.6860	100.0	299.0	0.3344	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	11.0	16.0	73.0	0.2192	0.1507	40.0	47.0	78.0	0.6026	0.5128	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	46.0	46	7.7805	0.0059	3356.2258	2326.3585	100.0	299.0	0.3344	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	39.0	46.0	78.0	0.5897	0.5	26.0	36.0	83.0	0.4337	0.3133	1.0
0.0	47.0	47	7.8061	0.0059	3367.2997	2334.0343	100.0	299.0	0.3344	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	25.0	36.0	83.0	0.4337	0.3012	1.0
0.0	48.0	48	7.8007	0.0059	3364.9411	2332.3994	100.0	299.0	0.3344	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	9.0	17.0	73.0	0.2329	0.1233	40.0	47.0	78.0	0.6026	0.5128	26.0	36.0	83.0	0.4337	0.3133	1.0
0.0	49.0	49	7.7781	0.0059	3355.2195	2325.6609	103.0	299.0	0.3445	78.0	0.2609	0.0	0.0	64.0	0.0	0.0	11.0	17.0	73.0	0.2329	0.1507	41.0	48.0	78.0	0.6154	0.5256	26.0	38.0	83.0	0.4578	0.3133	1.0
0.0	50.0	50	7.7726	0.0059	3352.8377	2324.0100	102.0	299.0	0.3411	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	51.0	51	7.8187	0.0059	3372.7324	2337.8000	102.0	299.0	0.3411	78.0	0.2609	0.0	0.0	64.0	0.0	0.0	11.0	17.0	73.0	0.2329	0.1507	40.0	47.0	78.0	0.6026	0.5128	27.0	38.0	83.0	0.4578	0.3253	1.0
0.0	52.0	52	7.8400	0.0059	3381.9094	2344.1609	100.0	299.0	0.3344	78.0	0.2609	0.0	0.0	64.0	0.0	0.0	10.0	16.0	73.0	0.2192	0.1370	40.0	47.0	78.0	0.6026	0.5128	28.0	37.0	83.0	0.4458	0.3373	1.0
0.0	53.0	53	7.8508	0.0059	3386.5587	2347.3836	100.0	299.0	0.3344	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	11.0	16.0	73.0	0.2192	0.1507	40.0	47.0	78.0	0.6026	0.5128	25.0	37.0	83.0	0.4458	0.3012	1.0
0.0	54.0	54	7.7833	0.0059	3357.4389	2327.1993	102.0	299.0	0.3411	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	40.0	47.0	78.0	0.6026	0.5128	27.0	37.0	83.0	0.4458	0.3253	1.0
0.0	55.0	55	7.8059	0.0059	3367.1922	2333.9598	100.0	299.0	0.3344	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	39.0	47.0	78.0	0.6026	0.5	27.0	36.0	83.0	0.4337	0.3253	1.0
0.0	56.0	56	7.7827	0.0059	3357.1780	2327.0184	101.0	299.0	0.3378	75.0	0.2508	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	25.0	37.0	83.0	0.4458	0.3012	1.0
0.0	57.0	57	7.8296	0.0059	3377.4155	2341.0460	100.0	299.0	0.3344	76.0	0.2542	0.0	0.0	64.0	0.0	0.0	10.0	16.0	73.0	0.2192	0.1370	40.0	47.0	78.0	0.6026	0.5128	26.0	37.0	83.0	0.4458	0.3133	1.0
0.0	58.0	58	7.8474	0.0059	3385.0930	2346.3677	102.0	299.0	0.3411	78.0	0.2609	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	28.0	38.0	83.0	0.4578	0.3373	1.0
0.0	59.0	59	7.8174	0.0059	3372.1641	2337.4061	100.0	299.0	0.3344	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	10.0	16.0	73.0	0.2192	0.1370	40.0	47.0	78.0	0.6026	0.5128	27.0	37.0	83.0	0.4458	0.3253	1.0
0.0	60.0	60	7.8233	0.0059	3374.6881	2339.1555	102.0	299.0	0.3411	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	40.0	47.0	78.0	0.6026	0.5128	27.0	38.0	83.0	0.4578	0.3253	1.0
0.0	61.0	61	7.8570	0.0059	3389.2507	2349.2496	102.0	299.0	0.3411	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	10.0	18.0	73.0	0.2466	0.1370	40.0	47.0	78.0	0.6026	0.5128	27.0	37.0	83.0	0.4458	0.3253	1.0
0.0	62.0	62	7.8322	0.0059	3378.5424	2341.8271	102.0	299.0	0.3411	77.0	0.2575	0.0	0.0	64.0	0.0	0.0	10.0	17.0	73.0	0.2329	0.1370	39.0	46.0	78.0	0.5897	0.5	28.0	39.0	83.0	0.4699	0.3373	1.0

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

donoway/ARC-Challenge_Llama-3.2-1B-6n1bjz24

ARC-Challenge_Llama-3.2-1B-6n1bjz24

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

donoway/
ARC-Challenge_Llama-3.2-1B-6n1bjz24