ARC-Easy_Llama-3.2-1B-arerciw5

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: 3.6297
• Model Preparation Time: 0.0069
• Mdl: 2984.8081
• Accumulated Loss: 2068.9113
• Correct Preds: 381.0
• Total Preds: 570.0
• Accuracy: 0.6684
• Correct Gen Preds: 368.0
• Gen Accuracy: 0.6456
• Correct Gen Preds 32: 108.0
• Correct Preds 32: 117.0
• Total Labels 32: 158.0
• Accuracy 32: 0.7405
• Gen Accuracy 32: 0.6835
• Correct Gen Preds 33: 116.0
• Correct Preds 33: 116.0
• Total Labels 33: 152.0
• Accuracy 33: 0.7632
• Gen Accuracy 33: 0.7632
• Correct Gen Preds 34: 67.0
• Correct Preds 34: 70.0
• Total Labels 34: 142.0
• Accuracy 34: 0.4930
• Gen Accuracy 34: 0.4718
• Correct Gen Preds 35: 77.0
• Correct Preds 35: 78.0
• Total Labels 35: 118.0
• Accuracy 35: 0.6610
• 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: 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	Correct Gen Preds 36	Correct Preds 36	Total Labels 36	Accuracy 36	Gen Accuracy 36
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	0.0	0.0	0.0	0.0	0.0
1.3337	1.0	2	1.4204	0.0069	1168.0072	809.6009	243.0	570.0	0.4263	243.0	0.4263	0.0	0.0	158.0	0.0	0.0	91.0	91.0	152.0	0.5987	0.5987	134.0	134.0	142.0	0.9437	0.9437	18.0	18.0	118.0	0.1525	0.1525	0.0	0.0	0.0	0.0	0.0
0.9513	2.0	4	1.5711	0.0069	1291.9860	895.5365	297.0	570.0	0.5211	297.0	0.5211	149.0	149.0	158.0	0.9430	0.9430	72.0	72.0	152.0	0.4737	0.4737	47.0	47.0	142.0	0.3310	0.3310	29.0	29.0	118.0	0.2458	0.2458	0.0	0.0	0.0	0.0	0.0
0.5156	3.0	6	1.1942	0.0069	982.0490	680.7045	341.0	570.0	0.5982	341.0	0.5982	45.0	45.0	158.0	0.2848	0.2848	101.0	101.0	152.0	0.6645	0.6645	107.0	107.0	142.0	0.7535	0.7535	88.0	88.0	118.0	0.7458	0.7458	0.0	0.0	0.0	0.0	0.0
0.0236	4.0	8	1.9337	0.0069	1590.1228	1102.1891	377.0	570.0	0.6614	377.0	0.6614	93.0	93.0	158.0	0.5886	0.5886	100.0	100.0	152.0	0.6579	0.6579	100.0	100.0	142.0	0.7042	0.7042	84.0	84.0	118.0	0.7119	0.7119	0.0	0.0	0.0	0.0	0.0
0.098	5.0	10	2.4705	0.0069	2031.5785	1408.1829	364.0	570.0	0.6386	363.0	0.6368	124.0	125.0	158.0	0.7911	0.7848	83.0	83.0	152.0	0.5461	0.5461	77.0	77.0	142.0	0.5423	0.5423	79.0	79.0	118.0	0.6695	0.6695	0.0	0.0	0.0	0.0	0.0
0.0699	6.0	12	3.2267	0.0069	2653.4710	1839.2459	375.0	570.0	0.6579	372.0	0.6526	114.0	117.0	158.0	0.7405	0.7215	103.0	103.0	152.0	0.6776	0.6776	78.0	78.0	142.0	0.5493	0.5493	77.0	77.0	118.0	0.6525	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	7.0	14	3.6297	0.0069	2984.8081	2068.9113	381.0	570.0	0.6684	368.0	0.6456	108.0	117.0	158.0	0.7405	0.6835	116.0	116.0	152.0	0.7632	0.7632	67.0	70.0	142.0	0.4930	0.4718	77.0	78.0	118.0	0.6610	0.6525	0.0	0.0	0.0	0.0	0.0
0.0	8.0	16	3.8663	0.0069	3179.3653	2203.7681	374.0	570.0	0.6561	341.0	0.5982	85.0	110.0	158.0	0.6962	0.5380	117.0	118.0	152.0	0.7763	0.7697	64.0	70.0	142.0	0.4930	0.4507	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	9.0	18	4.0266	0.0069	3311.2517	2295.1848	368.0	570.0	0.6456	327.0	0.5737	73.0	105.0	158.0	0.6646	0.4620	117.0	118.0	152.0	0.7763	0.7697	61.0	68.0	142.0	0.4789	0.4296	76.0	77.0	118.0	0.6525	0.6441	0.0	0.0	0.0	0.0	0.0
0.0	10.0	20	4.1711	0.0069	3430.0548	2377.5328	368.0	570.0	0.6456	326.0	0.5719	72.0	103.0	158.0	0.6519	0.4557	117.0	119.0	152.0	0.7829	0.7697	61.0	69.0	142.0	0.4859	0.4296	76.0	77.0	118.0	0.6525	0.6441	0.0	0.0	0.0	0.0	0.0
0.0	11.0	22	4.2348	0.0069	3482.4145	2413.8258	367.0	570.0	0.6439	327.0	0.5737	71.0	101.0	158.0	0.6392	0.4494	118.0	119.0	152.0	0.7829	0.7763	63.0	71.0	142.0	0.5	0.4437	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	12.0	24	4.3235	0.0069	3555.3314	2464.3680	366.0	570.0	0.6421	326.0	0.5719	73.0	104.0	158.0	0.6582	0.4620	117.0	118.0	152.0	0.7763	0.7697	61.0	68.0	142.0	0.4789	0.4296	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	13.0	26	4.3461	0.0069	3573.9396	2477.2662	370.0	570.0	0.6491	330.0	0.5789	74.0	105.0	158.0	0.6646	0.4684	117.0	118.0	152.0	0.7763	0.7697	64.0	71.0	142.0	0.5	0.4507	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	14.0	28	4.3956	0.0069	3614.6647	2505.4946	372.0	570.0	0.6526	331.0	0.5807	74.0	105.0	158.0	0.6646	0.4684	118.0	119.0	152.0	0.7829	0.7763	63.0	71.0	142.0	0.5	0.4437	76.0	77.0	118.0	0.6525	0.6441	0.0	0.0	0.0	0.0	0.0
0.0	15.0	30	4.4516	0.0069	3660.7412	2537.4324	366.0	570.0	0.6421	327.0	0.5737	72.0	102.0	158.0	0.6456	0.4557	117.0	118.0	152.0	0.7763	0.7697	64.0	71.0	142.0	0.5	0.4507	74.0	75.0	118.0	0.6356	0.6271	0.0	0.0	0.0	0.0	0.0
0.0	16.0	32	4.4475	0.0069	3657.3704	2535.0960	369.0	570.0	0.6474	330.0	0.5789	74.0	104.0	158.0	0.6582	0.4684	117.0	118.0	152.0	0.7763	0.7697	64.0	71.0	142.0	0.5	0.4507	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	17.0	34	4.4649	0.0069	3671.6638	2545.0034	369.0	570.0	0.6474	328.0	0.5754	73.0	104.0	158.0	0.6582	0.4620	116.0	118.0	152.0	0.7763	0.7632	64.0	71.0	142.0	0.5	0.4507	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	18.0	36	4.4897	0.0069	3692.0343	2559.1232	367.0	570.0	0.6439	328.0	0.5754	73.0	103.0	158.0	0.6519	0.4620	117.0	118.0	152.0	0.7763	0.7697	63.0	70.0	142.0	0.4930	0.4437	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	19.0	38	4.4832	0.0069	3686.6707	2555.4054	370.0	570.0	0.6491	331.0	0.5807	75.0	105.0	158.0	0.6646	0.4747	117.0	118.0	152.0	0.7763	0.7697	64.0	71.0	142.0	0.5	0.4507	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	20.0	40	4.4917	0.0069	3693.7120	2560.2860	370.0	570.0	0.6491	329.0	0.5772	73.0	105.0	158.0	0.6646	0.4620	118.0	119.0	152.0	0.7829	0.7763	63.0	70.0	142.0	0.4930	0.4437	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	21.0	42	4.4948	0.0069	3696.2223	2562.0261	370.0	570.0	0.6491	330.0	0.5789	73.0	104.0	158.0	0.6582	0.4620	117.0	118.0	152.0	0.7763	0.7697	64.0	71.0	142.0	0.5	0.4507	76.0	77.0	118.0	0.6525	0.6441	0.0	0.0	0.0	0.0	0.0
0.0	22.0	44	4.5041	0.0069	3703.9242	2567.3646	371.0	570.0	0.6509	332.0	0.5825	75.0	105.0	158.0	0.6646	0.4747	117.0	118.0	152.0	0.7763	0.7697	65.0	72.0	142.0	0.5070	0.4577	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	23.0	46	4.5023	0.0069	3702.4334	2566.3313	368.0	570.0	0.6456	331.0	0.5807	76.0	104.0	158.0	0.6582	0.4810	117.0	118.0	152.0	0.7763	0.7697	63.0	70.0	142.0	0.4930	0.4437	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	24.0	48	4.5165	0.0069	3714.0749	2574.4005	368.0	570.0	0.6456	331.0	0.5807	75.0	104.0	158.0	0.6582	0.4747	118.0	118.0	152.0	0.7763	0.7763	63.0	70.0	142.0	0.4930	0.4437	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	25.0	50	4.5122	0.0069	3710.5434	2571.9527	369.0	570.0	0.6474	329.0	0.5772	74.0	104.0	158.0	0.6582	0.4684	116.0	118.0	152.0	0.7763	0.7632	65.0	72.0	142.0	0.5070	0.4577	74.0	75.0	118.0	0.6356	0.6271	0.0	0.0	0.0	0.0	0.0
0.0	26.0	52	4.5475	0.0069	3739.5911	2592.0870	368.0	570.0	0.6456	329.0	0.5772	73.0	103.0	158.0	0.6519	0.4620	118.0	119.0	152.0	0.7829	0.7763	64.0	71.0	142.0	0.5	0.4507	74.0	75.0	118.0	0.6356	0.6271	0.0	0.0	0.0	0.0	0.0
0.0	27.0	54	4.5286	0.0069	3724.0209	2581.2946	368.0	570.0	0.6456	329.0	0.5772	74.0	104.0	158.0	0.6582	0.4684	117.0	118.0	152.0	0.7763	0.7697	63.0	70.0	142.0	0.4930	0.4437	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	28.0	56	4.5322	0.0069	3726.9841	2583.3485	368.0	570.0	0.6456	331.0	0.5807	75.0	103.0	158.0	0.6519	0.4747	116.0	117.0	152.0	0.7697	0.7632	66.0	73.0	142.0	0.5141	0.4648	74.0	75.0	118.0	0.6356	0.6271	0.0	0.0	0.0	0.0	0.0
0.0	29.0	58	4.5429	0.0069	3735.7961	2589.4565	368.0	570.0	0.6456	329.0	0.5772	74.0	104.0	158.0	0.6582	0.4684	117.0	118.0	152.0	0.7763	0.7697	63.0	70.0	142.0	0.4930	0.4437	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	30.0	60	4.5244	0.0069	3720.6018	2578.9247	367.0	570.0	0.6439	329.0	0.5772	74.0	103.0	158.0	0.6519	0.4684	117.0	118.0	152.0	0.7763	0.7697	63.0	70.0	142.0	0.4930	0.4437	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	31.0	62	4.5184	0.0069	3715.6023	2575.4593	369.0	570.0	0.6474	330.0	0.5789	74.0	104.0	158.0	0.6582	0.4684	117.0	118.0	152.0	0.7763	0.7697	64.0	71.0	142.0	0.5	0.4507	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	32.0	64	4.5386	0.0069	3732.2854	2587.0231	370.0	570.0	0.6491	332.0	0.5825	75.0	105.0	158.0	0.6646	0.4747	117.0	118.0	152.0	0.7763	0.7697	65.0	71.0	142.0	0.5	0.4577	75.0	76.0	118.0	0.6441	0.6356	0.0	0.0	0.0	0.0	0.0
0.0	33.0	66	4.5417	0.0069	3734.7736	2588.7478	369.0	570.0	0.6474	330.0	0.5789	74.0	104.0	158.0	0.6582	0.4684	117.0	118.0	152.0	0.7763	0.7697	65.0	72.0	142.0	0.5070	0.4577	74.0	75.0	118.0	0.6356	0.6271	0.0	0.0	0.0	0.0	0.0
0.0	34.0	68	4.5473	0.0069	3739.4472	2591.9873	371.0	570.0	0.6509	330.0	0.5789	72.0	104.0	158.0	0.6582	0.4557	118.0	119.0	152.0	0.7829	0.7763	64.0	71.0	142.0	0.5	0.4507	76.0	77.0	118.0	0.6525	0.6441	0.0	0.0	0.0	0.0	0.0
0.0	35.0	70	4.5106	0.0069	3709.2286	2571.0413	368.0	570.0	0.6456	330.0	0.5789	74.0	103.0	158.0	0.6519	0.4684	117.0	118.0	152.0	0.7763	0.7697	65.0	72.0	142.0	0.5070	0.4577	74.0	75.0	118.0	0.6356	0.6271	0.0	0.0	0.0	0.0	0.0
0.0	36.0	72	4.5517	0.0069	3743.0479	2594.4831	365.0	570.0	0.6404	327.0	0.5737	74.0	103.0	158.0	0.6519	0.4684	116.0	117.0	152.0	0.7697	0.7632	63.0	70.0	142.0	0.4930	0.4437	74.0	75.0	118.0	0.6356	0.6271	0.0	0.0	0.0	0.0	0.0
0.0	37.0	74	4.5277	0.0069	3723.2808	2580.7816	370.0	570.0	0.6491	331.0	0.5807	74.0	103.0	158.0	0.6519	0.4684	116.0	118.0	152.0	0.7763	0.7632	65.0	72.0	142.0	0.5070	0.4577	76.0	77.0	118.0	0.6525	0.6441	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