ARC-Easy_Llama-3.2-1B-r227hzq8

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 4.3885
• Model Preparation Time: 0.0059
• Mdl: 3608.8619
• Accumulated Loss: 2501.4725
• Correct Preds: 230.0
• Total Preds: 570.0
• Accuracy: 0.4035
• Correct Gen Preds: 130.0
• Gen Accuracy: 0.2281
• Correct Gen Preds 32: 82.0
• Correct Preds 32: 109.0
• Total Labels 32: 158.0
• Accuracy 32: 0.6899
• Gen Accuracy 32: 0.5190
• Correct Gen Preds 33: 24.0
• Correct Preds 33: 59.0
• Total Labels 33: 152.0
• Accuracy 33: 0.3882
• Gen Accuracy 33: 0.1579
• Correct Gen Preds 34: 0.0
• Correct Preds 34: 14.0
• Total Labels 34: 142.0
• Accuracy 34: 0.0986
• Gen Accuracy 34: 0.0
• Correct Gen Preds 35: 24.0
• Correct Preds 35: 48.0
• Total Labels 35: 118.0
• Accuracy 35: 0.4068
• Gen Accuracy 35: 0.2034
• Correct Gen Preds 36: 0.0
• Correct Preds 36: 0.0
• Total Labels 36: 0.0
• Accuracy 36: 0.0
• Gen Accuracy 36: 0.0

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: 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	Correct Gen Preds 36	Correct Preds 36	Total Labels 36	Accuracy 36	Gen Accuracy 36
No log	0	0	1.5354	0.0059	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	0.0	0.0	0.0	0.0	0.0
1.5507	1.0	3	1.7574	0.0059	1445.1619	1001.7099	158.0	570.0	0.2772	158.0	0.2772	158.0	158.0	158.0	1.0	1.0	0.0	0.0	152.0	0.0	0.0	0.0	0.0	142.0	0.0	0.0	0.0	0.0	118.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.41	2.0	6	1.4959	0.0059	1230.1581	852.6806	113.0	570.0	0.1982	0.0	0.0	0.0	0.0	158.0	0.0	0.0	0.0	0.0	152.0	0.0	0.0	0.0	0.0	142.0	0.0	0.0	0.0	113.0	118.0	0.9576	0.0	0.0	0.0	0.0	0.0	0.0
1.0576	3.0	9	1.7077	0.0059	1404.3174	973.3986	142.0	570.0	0.2491	0.0	0.0	0.0	94.0	158.0	0.5949	0.0	0.0	35.0	152.0	0.2303	0.0	0.0	3.0	142.0	0.0211	0.0	0.0	10.0	118.0	0.0847	0.0	0.0	0.0	0.0	0.0	0.0
1.0226	4.0	12	1.4658	0.0059	1205.3837	835.5083	172.0	570.0	0.3018	68.0	0.1193	14.0	60.0	158.0	0.3797	0.0886	14.0	32.0	152.0	0.2105	0.0921	20.0	38.0	142.0	0.2676	0.1408	20.0	42.0	118.0	0.3559	0.1695	0.0	0.0	0.0	0.0	0.0
0.3844	5.0	15	2.1761	0.0059	1789.4595	1240.3588	163.0	570.0	0.2860	2.0	0.0035	0.0	48.0	158.0	0.3038	0.0	1.0	61.0	152.0	0.4013	0.0066	0.0	10.0	142.0	0.0704	0.0	1.0	44.0	118.0	0.3729	0.0085	0.0	0.0	0.0	0.0	0.0
0.2725	6.0	18	2.4684	0.0059	2029.8647	1406.9950	213.0	570.0	0.3737	0.0	0.0	0.0	125.0	158.0	0.7911	0.0	0.0	54.0	152.0	0.3553	0.0	0.0	10.0	142.0	0.0704	0.0	0.0	24.0	118.0	0.2034	0.0	0.0	0.0	0.0	0.0	0.0
0.0205	7.0	21	2.6110	0.0059	2147.1166	1488.2678	193.0	570.0	0.3386	0.0	0.0	0.0	41.0	158.0	0.2595	0.0	0.0	53.0	152.0	0.3487	0.0	0.0	27.0	142.0	0.1901	0.0	0.0	72.0	118.0	0.6102	0.0	0.0	0.0	0.0	0.0	0.0
0.0026	8.0	24	3.0876	0.0059	2539.0238	1759.9172	214.0	570.0	0.3754	3.0	0.0053	1.0	80.0	158.0	0.5063	0.0063	2.0	83.0	152.0	0.5461	0.0132	0.0	22.0	142.0	0.1549	0.0	0.0	29.0	118.0	0.2458	0.0	0.0	0.0	0.0	0.0	0.0
0.0002	9.0	27	3.7583	0.0059	3090.5875	2142.2320	217.0	570.0	0.3807	71.0	0.1246	54.0	107.0	158.0	0.6772	0.3418	11.0	64.0	152.0	0.4211	0.0724	0.0	15.0	142.0	0.1056	0.0	6.0	31.0	118.0	0.2627	0.0508	0.0	0.0	0.0	0.0	0.0
0.0001	10.0	30	4.2182	0.0059	3468.7484	2404.3532	229.0	570.0	0.4018	117.0	0.2053	81.0	109.0	158.0	0.6899	0.5127	17.0	60.0	152.0	0.3947	0.1118	0.0	15.0	142.0	0.1056	0.0	19.0	45.0	118.0	0.3814	0.1610	0.0	0.0	0.0	0.0	0.0
0.0001	11.0	33	4.3885	0.0059	3608.8619	2501.4725	230.0	570.0	0.4035	130.0	0.2281	82.0	109.0	158.0	0.6899	0.5190	24.0	59.0	152.0	0.3882	0.1579	0.0	14.0	142.0	0.0986	0.0	24.0	48.0	118.0	0.4068	0.2034	0.0	0.0	0.0	0.0	0.0
0.0	12.0	36	4.4773	0.0059	3681.8295	2552.0498	228.0	570.0	0.4	130.0	0.2281	80.0	107.0	158.0	0.6772	0.5063	24.0	53.0	152.0	0.3487	0.1579	0.0	15.0	142.0	0.1056	0.0	26.0	53.0	118.0	0.4492	0.2203	0.0	0.0	0.0	0.0	0.0
0.0	13.0	39	4.5151	0.0059	3712.9366	2573.6116	223.0	570.0	0.3912	129.0	0.2263	78.0	105.0	158.0	0.6646	0.4937	23.0	49.0	152.0	0.3224	0.1513	0.0	15.0	142.0	0.1056	0.0	28.0	54.0	118.0	0.4576	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	14.0	42	4.5388	0.0059	3732.3879	2587.0941	227.0	570.0	0.3982	133.0	0.2333	78.0	107.0	158.0	0.6772	0.4937	23.0	49.0	152.0	0.3224	0.1513	0.0	17.0	142.0	0.1197	0.0	32.0	54.0	118.0	0.4576	0.2712	0.0	0.0	0.0	0.0	0.0
0.0	15.0	45	4.5674	0.0059	3755.9179	2603.4039	227.0	570.0	0.3982	130.0	0.2281	75.0	105.0	158.0	0.6646	0.4747	23.0	49.0	152.0	0.3224	0.1513	0.0	18.0	142.0	0.1268	0.0	32.0	55.0	118.0	0.4661	0.2712	0.0	0.0	0.0	0.0	0.0
0.0	16.0	48	4.5739	0.0059	3761.3227	2607.1502	225.0	570.0	0.3947	128.0	0.2246	73.0	105.0	158.0	0.6646	0.4620	25.0	50.0	152.0	0.3289	0.1645	0.0	16.0	142.0	0.1127	0.0	30.0	54.0	118.0	0.4576	0.2542	0.0	0.0	0.0	0.0	0.0
0.0	17.0	51	4.5932	0.0059	3777.1603	2618.1280	229.0	570.0	0.4018	130.0	0.2281	73.0	106.0	158.0	0.6709	0.4620	25.0	52.0	152.0	0.3421	0.1645	0.0	17.0	142.0	0.1197	0.0	32.0	54.0	118.0	0.4576	0.2712	0.0	0.0	0.0	0.0	0.0
0.0	18.0	54	4.5877	0.0059	3772.6195	2614.9806	227.0	570.0	0.3982	127.0	0.2228	71.0	105.0	158.0	0.6646	0.4494	25.0	51.0	152.0	0.3355	0.1645	0.0	17.0	142.0	0.1197	0.0	31.0	54.0	118.0	0.4576	0.2627	0.0	0.0	0.0	0.0	0.0
0.0	19.0	57	4.5848	0.0059	3770.2518	2613.3394	227.0	570.0	0.3982	128.0	0.2246	74.0	105.0	158.0	0.6646	0.4684	23.0	51.0	152.0	0.3355	0.1513	0.0	16.0	142.0	0.1127	0.0	31.0	55.0	118.0	0.4661	0.2627	0.0	0.0	0.0	0.0	0.0
0.0	20.0	60	4.5989	0.0059	3781.8769	2621.3973	226.0	570.0	0.3965	128.0	0.2246	73.0	105.0	158.0	0.6646	0.4620	24.0	51.0	152.0	0.3355	0.1579	0.0	16.0	142.0	0.1127	0.0	31.0	54.0	118.0	0.4576	0.2627	0.0	0.0	0.0	0.0	0.0
0.0	21.0	63	4.5908	0.0059	3775.1588	2616.7407	227.0	570.0	0.3982	129.0	0.2263	73.0	105.0	158.0	0.6646	0.4620	24.0	50.0	152.0	0.3289	0.1579	0.0	16.0	142.0	0.1127	0.0	32.0	56.0	118.0	0.4746	0.2712	0.0	0.0	0.0	0.0	0.0

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1