ARC-Easy_Llama-3.2-1B-w1lhw9kp

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: 2.1597
• Model Preparation Time: 0.0056
• Mdl: 1776.0078
• Accumulated Loss: 1231.0348
• Correct Preds: 432.0
• Total Preds: 570.0
• Accuracy: 0.7579
• Correct Gen Preds: 431.0
• Gen Accuracy: 0.7561
• Correct Gen Preds 32: 128.0
• Correct Preds 32: 129.0
• Total Labels 32: 158.0
• Accuracy 32: 0.8165
• Gen Accuracy 32: 0.8101
• Correct Gen Preds 33: 120.0
• Correct Preds 33: 120.0
• Total Labels 33: 152.0
• Accuracy 33: 0.7895
• Gen Accuracy 33: 0.7895
• Correct Gen Preds 34: 106.0
• Correct Preds 34: 106.0
• Total Labels 34: 142.0
• Accuracy 34: 0.7465
• Gen Accuracy 34: 0.7465
• Correct Gen Preds 35: 77.0
• Correct Preds 35: 77.0
• Total Labels 35: 118.0
• Accuracy 35: 0.6525
• Gen Accuracy 35: 0.6525
• 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	0.0056	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
0.7522	1.0	28	0.7367	0.0056	605.7885	419.9006	419.0	570.0	0.7351	402.0	0.7053	103.0	114.0	158.0	0.7215	0.6519	122.0	122.0	152.0	0.8026	0.8026	108.0	109.0	142.0	0.7676	0.7606	69.0	74.0	118.0	0.6271	0.5847	0.0	0.0	0.0	0.0	0.0
0.4231	2.0	56	0.7759	0.0056	638.0789	442.2826	424.0	570.0	0.7439	423.0	0.7421	134.0	135.0	158.0	0.8544	0.8481	107.0	107.0	152.0	0.7039	0.7039	100.0	100.0	142.0	0.7042	0.7042	82.0	82.0	118.0	0.6949	0.6949	0.0	0.0	0.0	0.0	0.0
0.0288	3.0	84	1.0058	0.0056	827.0667	573.2790	419.0	570.0	0.7351	419.0	0.7351	117.0	117.0	158.0	0.7405	0.7405	117.0	117.0	152.0	0.7697	0.7697	111.0	111.0	142.0	0.7817	0.7817	74.0	74.0	118.0	0.6271	0.6271	0.0	0.0	0.0	0.0	0.0
0.0006	4.0	112	1.7356	0.0056	1427.2623	989.3028	423.0	570.0	0.7421	423.0	0.7421	105.0	105.0	158.0	0.6646	0.6646	117.0	117.0	152.0	0.7697	0.7697	115.0	115.0	142.0	0.8099	0.8099	86.0	86.0	118.0	0.7288	0.7288	0.0	0.0	0.0	0.0	0.0
0.0003	5.0	140	2.1692	0.0056	1783.7864	1236.4265	429.0	570.0	0.7526	429.0	0.7526	126.0	126.0	158.0	0.7975	0.7975	116.0	116.0	152.0	0.7632	0.7632	106.0	106.0	142.0	0.7465	0.7465	81.0	81.0	118.0	0.6864	0.6864	0.0	0.0	0.0	0.0	0.0
0.0002	6.0	168	2.1597	0.0056	1776.0078	1231.0348	432.0	570.0	0.7579	431.0	0.7561	128.0	129.0	158.0	0.8165	0.8101	120.0	120.0	152.0	0.7895	0.7895	106.0	106.0	142.0	0.7465	0.7465	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	7.0	196	2.3405	0.0056	1924.6805	1334.0869	423.0	570.0	0.7421	422.0	0.7404	116.0	117.0	158.0	0.7405	0.7342	115.0	115.0	152.0	0.7566	0.7566	108.0	108.0	142.0	0.7606	0.7606	83.0	83.0	118.0	0.7034	0.7034	0.0	0.0	0.0	0.0	0.0
0.0381	8.0	224	2.3965	0.0056	1970.7046	1365.9884	417.0	570.0	0.7316	416.0	0.7298	119.0	120.0	158.0	0.7595	0.7532	114.0	114.0	152.0	0.75	0.75	105.0	105.0	142.0	0.7394	0.7394	78.0	78.0	118.0	0.6610	0.6610	0.0	0.0	0.0	0.0	0.0
0.0	9.0	252	2.4291	0.0056	1997.5619	1384.6044	418.0	570.0	0.7333	417.0	0.7316	120.0	121.0	158.0	0.7658	0.7595	115.0	115.0	152.0	0.7566	0.7566	105.0	105.0	142.0	0.7394	0.7394	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	10.0	280	2.4664	0.0056	2028.2465	1405.8733	417.0	570.0	0.7316	416.0	0.7298	119.0	120.0	158.0	0.7595	0.7532	116.0	116.0	152.0	0.7632	0.7632	104.0	104.0	142.0	0.7324	0.7324	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	11.0	308	2.4742	0.0056	2034.5929	1410.2723	416.0	570.0	0.7298	415.0	0.7281	119.0	120.0	158.0	0.7595	0.7532	115.0	115.0	152.0	0.7566	0.7566	104.0	104.0	142.0	0.7324	0.7324	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	12.0	336	2.4880	0.0056	2045.9589	1418.1506	420.0	570.0	0.7368	419.0	0.7351	120.0	121.0	158.0	0.7658	0.7595	116.0	116.0	152.0	0.7632	0.7632	106.0	106.0	142.0	0.7465	0.7465	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	13.0	364	2.4972	0.0056	2053.5491	1423.4117	417.0	570.0	0.7316	416.0	0.7298	119.0	120.0	158.0	0.7595	0.7532	115.0	115.0	152.0	0.7566	0.7566	105.0	105.0	142.0	0.7394	0.7394	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	14.0	392	2.5111	0.0056	2065.0014	1431.3499	417.0	570.0	0.7316	416.0	0.7298	119.0	120.0	158.0	0.7595	0.7532	115.0	115.0	152.0	0.7566	0.7566	105.0	105.0	142.0	0.7394	0.7394	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	15.0	420	2.5096	0.0056	2063.7478	1430.4810	420.0	570.0	0.7368	419.0	0.7351	119.0	120.0	158.0	0.7595	0.7532	116.0	116.0	152.0	0.7632	0.7632	106.0	106.0	142.0	0.7465	0.7465	78.0	78.0	118.0	0.6610	0.6610	0.0	0.0	0.0	0.0	0.0
0.0	16.0	448	2.5157	0.0056	2068.7736	1433.9646	419.0	570.0	0.7351	418.0	0.7333	119.0	120.0	158.0	0.7595	0.7532	116.0	116.0	152.0	0.7632	0.7632	106.0	106.0	142.0	0.7465	0.7465	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	17.0	476	2.5341	0.0056	2083.8433	1444.4101	417.0	570.0	0.7316	416.0	0.7298	120.0	121.0	158.0	0.7658	0.7595	115.0	115.0	152.0	0.7566	0.7566	104.0	104.0	142.0	0.7324	0.7324	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	18.0	504	2.5326	0.0056	2082.6165	1443.5598	419.0	570.0	0.7351	418.0	0.7333	119.0	120.0	158.0	0.7595	0.7532	116.0	116.0	152.0	0.7632	0.7632	105.0	105.0	142.0	0.7394	0.7394	78.0	78.0	118.0	0.6610	0.6610	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