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: cosine
lr_scheduler_warmup_ratio: 0.01
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
No log	0	0	1.5354	0.0069	1262.6022	875.1692	172.0	570.0	0.3018	170.0	0.2982	154.0	154.0	158.0	0.9747	0.9747	0.0	0.0	152.0	0.0	0.0	15.0	17.0	142.0	0.1197	0.1056	1.0	1.0	118.0	0.0085	0.0085
1.4592	1.0	1	1.5354	0.0069	1262.6022	875.1692	172.0	570.0	0.3018	170.0	0.2982	154.0	154.0	158.0	0.9747	0.9747	0.0	0.0	152.0	0.0	0.0	15.0	17.0	142.0	0.1197	0.1056	1.0	1.0	118.0	0.0085	0.0085
1.4587	2.0	2	2.8572	0.0069	2349.6051	1628.6221	188.0	570.0	0.3298	188.0	0.3298	0.0	0.0	158.0	0.0	0.0	46.0	46.0	152.0	0.3026	0.3026	141.0	141.0	142.0	0.9930	0.9930	1.0	1.0	118.0	0.0085	0.0085
1.7615	3.0	3	1.5150	0.0069	1245.8152	863.5333	173.0	570.0	0.3035	173.0	0.3035	0.0	0.0	158.0	0.0	0.0	151.0	151.0	152.0	0.9934	0.9934	8.0	8.0	142.0	0.0563	0.0563	14.0	14.0	118.0	0.1186	0.1186
0.683	4.0	4	1.3806	0.0069	1135.3136	786.9394	307.0	570.0	0.5386	254.0	0.4456	39.0	59.0	158.0	0.3734	0.2468	107.0	126.0	152.0	0.8289	0.7039	76.0	84.0	142.0	0.5915	0.5352	32.0	38.0	118.0	0.3220	0.2712
0.0591	5.0	5	1.8312	0.0069	1505.8471	1043.7737	356.0	570.0	0.6246	262.0	0.4596	53.0	98.0	158.0	0.6203	0.3354	98.0	115.0	152.0	0.7566	0.6447	69.0	92.0	142.0	0.6479	0.4859	42.0	51.0	118.0	0.4322	0.3559
0.0003	6.0	6	2.3233	0.0069	1910.5098	1324.2645	353.0	570.0	0.6193	288.0	0.5053	64.0	97.0	158.0	0.6139	0.4051	103.0	113.0	152.0	0.7434	0.6776	75.0	90.0	142.0	0.6338	0.5282	46.0	53.0	118.0	0.4492	0.3898
0.0	7.0	7	2.6634	0.0069	2190.2029	1518.1330	366.0	570.0	0.6421	306.0	0.5368	66.0	101.0	158.0	0.6392	0.4177	108.0	115.0	152.0	0.7566	0.7105	81.0	95.0	142.0	0.6690	0.5704	51.0	55.0	118.0	0.4661	0.4322
0.0	8.0	8	2.9283	0.0069	2408.0786	1669.1529	365.0	570.0	0.6404	313.0	0.5491	67.0	101.0	158.0	0.6392	0.4241	109.0	113.0	152.0	0.7434	0.7171	87.0	96.0	142.0	0.6761	0.6127	50.0	55.0	118.0	0.4661	0.4237
0.0	9.0	9	3.1394	0.0069	2581.6660	1789.4745	370.0	570.0	0.6491	318.0	0.5579	70.0	104.0	158.0	0.6582	0.4430	110.0	115.0	152.0	0.7566	0.7237	88.0	97.0	142.0	0.6831	0.6197	50.0	54.0	118.0	0.4576	0.4237
0.0	10.0	10	3.2952	0.0069	2709.7573	1878.2607	368.0	570.0	0.6456	314.0	0.5509	73.0	101.0	158.0	0.6392	0.4620	109.0	114.0	152.0	0.75	0.7171	86.0	98.0	142.0	0.6901	0.6056	46.0	55.0	118.0	0.4661	0.3898
0.0	11.0	11	3.4102	0.0069	2804.3076	1943.7979	366.0	570.0	0.6421	318.0	0.5579	74.0	100.0	158.0	0.6329	0.4684	109.0	114.0	152.0	0.75	0.7171	89.0	98.0	142.0	0.6901	0.6268	46.0	54.0	118.0	0.4576	0.3898
0.0	12.0	12	3.4933	0.0069	2872.6570	1991.1741	366.0	570.0	0.6421	320.0	0.5614	74.0	100.0	158.0	0.6329	0.4684	110.0	114.0	152.0	0.75	0.7237	90.0	98.0	142.0	0.6901	0.6338	46.0	54.0	118.0	0.4576	0.3898
0.0	13.0	13	3.5624	0.0069	2929.5074	2030.5798	364.0	570.0	0.6386	318.0	0.5579	75.0	100.0	158.0	0.6329	0.4747	109.0	113.0	152.0	0.7434	0.7171	88.0	97.0	142.0	0.6831	0.6197	46.0	54.0	118.0	0.4576	0.3898
0.0	14.0	14	3.6095	0.0069	2968.2088	2057.4056	365.0	570.0	0.6404	318.0	0.5579	71.0	100.0	158.0	0.6329	0.4494	111.0	114.0	152.0	0.75	0.7303	90.0	97.0	142.0	0.6831	0.6338	46.0	54.0	118.0	0.4576	0.3898
0.0	15.0	15	3.6542	0.0069	3004.9703	2082.8867	368.0	570.0	0.6456	319.0	0.5596	73.0	102.0	158.0	0.6456	0.4620	110.0	113.0	152.0	0.7434	0.7237	90.0	98.0	142.0	0.6901	0.6338	46.0	55.0	118.0	0.4661	0.3898
0.0	16.0	16	3.6640	0.0069	3013.0252	2088.4699	367.0	570.0	0.6439	321.0	0.5632	73.0	101.0	158.0	0.6392	0.4620	111.0	114.0	152.0	0.75	0.7303	91.0	98.0	142.0	0.6901	0.6408	46.0	54.0	118.0	0.4576	0.3898
0.0	17.0	17	3.6991	0.0069	3041.8667	2108.4613	369.0	570.0	0.6474	321.0	0.5632	76.0	103.0	158.0	0.6519	0.4810	109.0	113.0	152.0	0.7434	0.7171	90.0	98.0	142.0	0.6901	0.6338	46.0	55.0	118.0	0.4661	0.3898
0.0	18.0	18	3.7206	0.0069	3059.5550	2120.7219	370.0	570.0	0.6491	321.0	0.5632	77.0	104.0	158.0	0.6582	0.4873	109.0	113.0	152.0	0.7434	0.7171	89.0	97.0	142.0	0.6831	0.6268	46.0	56.0	118.0	0.4746	0.3898
0.0	19.0	19	3.7281	0.0069	3065.7453	2125.0127	368.0	570.0	0.6456	320.0	0.5614	74.0	102.0	158.0	0.6456	0.4684	110.0	114.0	152.0	0.75	0.7237	90.0	98.0	142.0	0.6901	0.6338	46.0	54.0	118.0	0.4576	0.3898
0.0	20.0	20	3.7380	0.0069	3073.8754	2130.6481	369.0	570.0	0.6474	321.0	0.5632	77.0	102.0	158.0	0.6456	0.4873	109.0	114.0	152.0	0.75	0.7171	90.0	97.0	142.0	0.6831	0.6338	45.0	56.0	118.0	0.4746	0.3814
0.0	21.0	21	3.7385	0.0069	3074.3332	2130.9654	371.0	570.0	0.6509	326.0	0.5719	79.0	103.0	158.0	0.6519	0.5	110.0	113.0	152.0	0.7434	0.7237	91.0	99.0	142.0	0.6972	0.6408	46.0	56.0	118.0	0.4746	0.3898
0.0	22.0	22	3.7640	0.0069	3095.2993	2145.4980	366.0	570.0	0.6421	319.0	0.5596	75.0	101.0	158.0	0.6392	0.4747	108.0	113.0	152.0	0.7434	0.7105	90.0	97.0	142.0	0.6831	0.6338	46.0	55.0	118.0	0.4661	0.3898
0.0	23.0	23	3.7726	0.0069	3102.3483	2150.3840	367.0	570.0	0.6439	325.0	0.5702	81.0	102.0	158.0	0.6456	0.5127	108.0	112.0	152.0	0.7368	0.7105	90.0	98.0	142.0	0.6901	0.6338	46.0	55.0	118.0	0.4661	0.3898
0.0	24.0	24	3.7770	0.0069	3105.9931	2152.9104	368.0	570.0	0.6456	321.0	0.5632	76.0	102.0	158.0	0.6456	0.4810	109.0	112.0	152.0	0.7368	0.7171	90.0	98.0	142.0	0.6901	0.6338	46.0	56.0	118.0	0.4746	0.3898
0.0	25.0	25	3.7813	0.0069	3109.4856	2155.3312	367.0	570.0	0.6439	322.0	0.5649	78.0	103.0	158.0	0.6519	0.4937	109.0	112.0	152.0	0.7368	0.7171	90.0	98.0	142.0	0.6901	0.6338	45.0	54.0	118.0	0.4576	0.3814
0.0	26.0	26	3.7764	0.0069	3105.4752	2152.5513	367.0	570.0	0.6439	322.0	0.5649	79.0	103.0	158.0	0.6519	0.5	109.0	112.0	152.0	0.7368	0.7171	89.0	97.0	142.0	0.6831	0.6268	45.0	55.0	118.0	0.4661	0.3814
0.0	27.0	27	3.7828	0.0069	3110.7617	2156.2157	365.0	570.0	0.6404	321.0	0.5632	79.0	102.0	158.0	0.6456	0.5	108.0	112.0	152.0	0.7368	0.7105	89.0	97.0	142.0	0.6831	0.6268	45.0	54.0	118.0	0.4576	0.3814
0.0	28.0	28	3.7887	0.0069	3115.5792	2159.5549	367.0	570.0	0.6439	321.0	0.5632	78.0	102.0	158.0	0.6456	0.4937	108.0	111.0	152.0	0.7303	0.7105	90.0	99.0	142.0	0.6972	0.6338	45.0	55.0	118.0	0.4661	0.3814
0.0	29.0	29	3.7980	0.0069	3123.2559	2164.8760	366.0	570.0	0.6421	324.0	0.5684	79.0	102.0	158.0	0.6456	0.5	109.0	112.0	152.0	0.7368	0.7171	91.0	98.0	142.0	0.6901	0.6408	45.0	54.0	118.0	0.4576	0.3814
0.0	30.0	30	3.7857	0.0069	3113.0984	2157.8354	369.0	570.0	0.6474	325.0	0.5702	79.0	102.0	158.0	0.6456	0.5	110.0	114.0	152.0	0.75	0.7237	92.0	99.0	142.0	0.6972	0.6479	44.0	54.0	118.0	0.4576	0.3729
0.0	31.0	31	3.8105	0.0069	3133.4788	2171.9620	367.0	570.0	0.6439	323.0	0.5667	78.0	103.0	158.0	0.6519	0.4937	109.0	111.0	152.0	0.7303	0.7171	91.0	98.0	142.0	0.6901	0.6408	45.0	55.0	118.0	0.4661	0.3814
0.0	32.0	32	3.7983	0.0069	3123.4747	2165.0277	368.0	570.0	0.6456	323.0	0.5667	80.0	103.0	158.0	0.6519	0.5063	109.0	112.0	152.0	0.7368	0.7171	89.0	98.0	142.0	0.6901	0.6268	45.0	55.0	118.0	0.4661	0.3814
0.0	33.0	33	3.7838	0.0069	3111.5678	2156.7744	368.0	570.0	0.6456	320.0	0.5614	77.0	102.0	158.0	0.6456	0.4873	108.0	112.0	152.0	0.7368	0.7105	90.0	98.0	142.0	0.6901	0.6338	45.0	56.0	118.0	0.4746	0.3814
0.0	34.0	34	3.8000	0.0069	3124.8632	2165.9901	366.0	570.0	0.6421	320.0	0.5614	79.0	103.0	158.0	0.6519	0.5	108.0	111.0	152.0	0.7303	0.7105	88.0	97.0	142.0	0.6831	0.6197	45.0	55.0	118.0	0.4661	0.3814
0.0	35.0	35	3.8131	0.0069	3135.6651	2173.4774	363.0	570.0	0.6368	320.0	0.5614	79.0	102.0	158.0	0.6456	0.5	107.0	110.0	152.0	0.7237	0.7039	89.0	97.0	142.0	0.6831	0.6268	45.0	54.0	118.0	0.4576	0.3814
0.0	36.0	36	3.7965	0.0069	3121.9935	2164.0010	367.0	570.0	0.6439	322.0	0.5649	79.0	102.0	158.0	0.6456	0.5	109.0	113.0	152.0	0.7434	0.7171	89.0	98.0	142.0	0.6901	0.6268	45.0	54.0	118.0	0.4576	0.3814
0.0	37.0	37	3.7996	0.0069	3124.5287	2165.7583	368.0	570.0	0.6456	322.0	0.5649	79.0	103.0	158.0	0.6519	0.5	109.0	113.0	152.0	0.7434	0.7171	89.0	97.0	142.0	0.6831	0.6268	45.0	55.0	118.0	0.4661	0.3814
0.0	38.0	38	3.7855	0.0069	3112.9473	2157.7307	369.0	570.0	0.6474	324.0	0.5684	79.0	103.0	158.0	0.6519	0.5	110.0	113.0	152.0	0.7434	0.7237	91.0	99.0	142.0	0.6972	0.6408	44.0	54.0	118.0	0.4576	0.3729
0.0	39.0	39	3.7976	0.0069	3122.9250	2164.6467	366.0	570.0	0.6421	322.0	0.5649	79.0	102.0	158.0	0.6456	0.5	108.0	111.0	152.0	0.7303	0.7105	89.0	97.0	142.0	0.6831	0.6268	46.0	56.0	118.0	0.4746	0.3898
0.0	40.0	40	3.7913	0.0069	3117.7141	2161.0348	366.0	570.0	0.6421	323.0	0.5667	79.0	102.0	158.0	0.6456	0.5	109.0	112.0	152.0	0.7368	0.7171	90.0	98.0	142.0	0.6901	0.6338	45.0	54.0	118.0	0.4576	0.3814
0.0	41.0	41	3.8044	0.0069	3128.4659	2168.4873	370.0	570.0	0.6491	321.0	0.5632	78.0	103.0	158.0	0.6519	0.4937	107.0	112.0	152.0	0.7368	0.7039	91.0	99.0	142.0	0.6972	0.6408	45.0	56.0	118.0	0.4746	0.3814
0.0	42.0	42	3.8034	0.0069	3127.6742	2167.9386	367.0	570.0	0.6439	323.0	0.5667	79.0	103.0	158.0	0.6519	0.5	110.0	113.0	152.0	0.7434	0.7237	89.0	96.0	142.0	0.6761	0.6268	45.0	55.0	118.0	0.4661	0.3814
0.0	43.0	43	3.7958	0.0069	3121.3983	2163.5884	367.0	570.0	0.6439	323.0	0.5667	80.0	102.0	158.0	0.6456	0.5063	108.0	112.0	152.0	0.7368	0.7105	90.0	97.0	142.0	0.6831	0.6338	45.0	56.0	118.0	0.4746	0.3814
0.0	44.0	44	3.8052	0.0069	3129.1145	2168.9369	366.0	570.0	0.6421	321.0	0.5632	77.0	101.0	158.0	0.6392	0.4873	108.0	112.0	152.0	0.7368	0.7105	91.0	98.0	142.0	0.6901	0.6408	45.0	55.0	118.0	0.4661	0.3814
0.0	45.0	45	3.7989	0.0069	3123.9498	2165.3570	367.0	570.0	0.6439	324.0	0.5684	79.0	102.0	158.0	0.6456	0.5	110.0	113.0	152.0	0.7434	0.7237	90.0	98.0	142.0	0.6901	0.6338	45.0	54.0	118.0	0.4576	0.3814
0.0	46.0	46	3.8045	0.0069	3128.6029	2168.5823	369.0	570.0	0.6474	322.0	0.5649	76.0	102.0	158.0	0.6456	0.4810	109.0	113.0	152.0	0.7434	0.7171	92.0	99.0	142.0	0.6972	0.6479	45.0	55.0	118.0	0.4661	0.3814
0.0	47.0	47	3.8041	0.0069	3128.2620	2168.3460	367.0	570.0	0.6439	324.0	0.5684	81.0	103.0	158.0	0.6519	0.5127	108.0	112.0	152.0	0.7368	0.7105	90.0	98.0	142.0	0.6901	0.6338	45.0	54.0	118.0	0.4576	0.3814
0.0	48.0	48	3.7913	0.0069	3117.7010	2161.0257	367.0	570.0	0.6439	321.0	0.5632	77.0	102.0	158.0	0.6456	0.4873	108.0	112.0	152.0	0.7368	0.7105	91.0	99.0	142.0	0.6972	0.6408	45.0	54.0	118.0	0.4576	0.3814
0.0	49.0	49	3.8082	0.0069	3131.6407	2170.6880	365.0	570.0	0.6404	321.0	0.5632	78.0	101.0	158.0	0.6392	0.4937	108.0	112.0	152.0	0.7368	0.7105	90.0	98.0	142.0	0.6901	0.6338	45.0	54.0	118.0	0.4576	0.3814
0.0	50.0	50	3.8087	0.0069	3132.0417	2170.9659	367.0	570.0	0.6439	322.0	0.5649	78.0	103.0	158.0	0.6519	0.4937	109.0	112.0	152.0	0.7368	0.7171	90.0	98.0	142.0	0.6901	0.6338	45.0	54.0	118.0	0.4576	0.3814
0.0	51.0	51	3.7933	0.0069	3119.3595	2162.1753	368.0	570.0	0.6456	321.0	0.5632	77.0	102.0	158.0	0.6456	0.4873	109.0	112.0	152.0	0.7368	0.7171	90.0	98.0	142.0	0.6901	0.6338	45.0	56.0	118.0	0.4746	0.3814

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

donoway/ARC-Easy_Llama-3.2-1B-oqrx1b71

ARC-Easy_Llama-3.2-1B-oqrx1b71

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

donoway/
ARC-Easy_Llama-3.2-1B-oqrx1b71