ARC-Easy_Llama-3.2-1B-ufd34f01

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: 3.0193
• Model Preparation Time: 0.0061
• Mdl: 2482.8831
• Accumulated Loss: 1721.0034
• Correct Preds: 359.0
• Total Preds: 570.0
• Accuracy: 0.6298
• Correct Gen Preds: 352.0
• Gen Accuracy: 0.6175
• Correct Gen Preds 32: 124.0
• Correct Preds 32: 126.0
• Total Labels 32: 158.0
• Accuracy 32: 0.7975
• Gen Accuracy 32: 0.7848
• Correct Gen Preds 33: 110.0
• Correct Preds 33: 110.0
• Total Labels 33: 152.0
• Accuracy 33: 0.7237
• Gen Accuracy 33: 0.7237
• Correct Gen Preds 34: 81.0
• Correct Preds 34: 85.0
• Total Labels 34: 142.0
• Accuracy 34: 0.5986
• Gen Accuracy 34: 0.5704
• Correct Gen Preds 35: 37.0
• Correct Preds 35: 38.0
• Total Labels 35: 118.0
• Accuracy 35: 0.3220
• Gen Accuracy 35: 0.3136
• 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	0.0061	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
1.5057	1.0	1	1.5354	0.0061	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
1.5112	2.0	2	2.5224	0.0061	2074.2721	1437.7759	226.0	570.0	0.3965	226.0	0.3965	0.0	0.0	158.0	0.0	0.0	123.0	123.0	152.0	0.8092	0.8092	103.0	103.0	142.0	0.7254	0.7254	0.0	0.0	118.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.7603	3.0	3	1.3081	0.0061	1075.7123	745.6270	227.0	570.0	0.3982	227.0	0.3982	0.0	0.0	158.0	0.0	0.0	140.0	140.0	152.0	0.9211	0.9211	49.0	49.0	142.0	0.3451	0.3451	38.0	38.0	118.0	0.3220	0.3220	0.0	0.0	0.0	0.0	0.0
0.5467	4.0	4	1.3336	0.0061	1096.7059	760.1786	334.0	570.0	0.5860	332.0	0.5825	74.0	76.0	158.0	0.4810	0.4684	128.0	128.0	152.0	0.8421	0.8421	89.0	89.0	142.0	0.6268	0.6268	41.0	41.0	118.0	0.3475	0.3475	0.0	0.0	0.0	0.0	0.0
0.0251	5.0	5	2.4343	0.0061	2001.8424	1387.5714	348.0	570.0	0.6105	340.0	0.5965	110.0	116.0	158.0	0.7342	0.6962	111.0	111.0	152.0	0.7303	0.7303	81.0	83.0	142.0	0.5845	0.5704	38.0	38.0	118.0	0.3220	0.3220	0.0	0.0	0.0	0.0	0.0
0.0	6.0	6	3.0193	0.0061	2482.8831	1721.0034	359.0	570.0	0.6298	352.0	0.6175	124.0	126.0	158.0	0.7975	0.7848	110.0	110.0	152.0	0.7237	0.7237	81.0	85.0	142.0	0.5986	0.5704	37.0	38.0	118.0	0.3220	0.3136	0.0	0.0	0.0	0.0	0.0
0.0	7.0	7	3.2734	0.0061	2691.8214	1865.8284	358.0	570.0	0.6281	346.0	0.6070	124.0	126.0	158.0	0.7975	0.7848	110.0	110.0	152.0	0.7237	0.7237	75.0	83.0	142.0	0.5845	0.5282	37.0	39.0	118.0	0.3305	0.3136	0.0	0.0	0.0	0.0	0.0
0.0	8.0	8	3.4379	0.0061	2827.1193	1959.6098	353.0	570.0	0.6193	338.0	0.5930	124.0	126.0	158.0	0.7975	0.7848	105.0	108.0	152.0	0.7105	0.6908	73.0	82.0	142.0	0.5775	0.5141	36.0	37.0	118.0	0.3136	0.3051	0.0	0.0	0.0	0.0	0.0
0.0	9.0	9	3.5233	0.0061	2897.3586	2008.2960	350.0	570.0	0.6140	330.0	0.5789	124.0	126.0	158.0	0.7975	0.7848	102.0	105.0	152.0	0.6908	0.6711	69.0	82.0	142.0	0.5775	0.4859	35.0	37.0	118.0	0.3136	0.2966	0.0	0.0	0.0	0.0	0.0
0.0	10.0	10	3.6239	0.0061	2980.0968	2065.6457	342.0	570.0	0.6	321.0	0.5632	125.0	127.0	158.0	0.8038	0.7911	101.0	103.0	152.0	0.6776	0.6645	67.0	79.0	142.0	0.5563	0.4718	28.0	33.0	118.0	0.2797	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	11.0	11	3.6994	0.0061	3042.1240	2108.6397	343.0	570.0	0.6018	321.0	0.5632	126.0	128.0	158.0	0.8101	0.7975	101.0	104.0	152.0	0.6842	0.6645	64.0	77.0	142.0	0.5423	0.4507	30.0	34.0	118.0	0.2881	0.2542	0.0	0.0	0.0	0.0	0.0
0.0	12.0	12	3.7327	0.0061	3069.5408	2127.6436	340.0	570.0	0.5965	314.0	0.5509	125.0	128.0	158.0	0.8101	0.7911	95.0	101.0	152.0	0.6645	0.625	65.0	77.0	142.0	0.5423	0.4577	29.0	34.0	118.0	0.2881	0.2458	0.0	0.0	0.0	0.0	0.0
0.0	13.0	13	3.7788	0.0061	3107.4349	2153.9098	337.0	570.0	0.5912	310.0	0.5439	124.0	128.0	158.0	0.8101	0.7848	95.0	99.0	152.0	0.6513	0.625	62.0	75.0	142.0	0.5282	0.4366	29.0	35.0	118.0	0.2966	0.2458	0.0	0.0	0.0	0.0	0.0
0.0	14.0	14	3.8434	0.0061	3160.5389	2190.7186	333.0	570.0	0.5842	306.0	0.5368	123.0	127.0	158.0	0.8038	0.7785	94.0	99.0	152.0	0.6513	0.6184	62.0	75.0	142.0	0.5282	0.4366	27.0	32.0	118.0	0.2712	0.2288	0.0	0.0	0.0	0.0	0.0
0.0	15.0	15	3.8505	0.0061	3166.4407	2194.8094	335.0	570.0	0.5877	310.0	0.5439	123.0	127.0	158.0	0.8038	0.7785	96.0	99.0	152.0	0.6513	0.6316	63.0	77.0	142.0	0.5423	0.4437	28.0	32.0	118.0	0.2712	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	16.0	16	3.8673	0.0061	3180.2457	2204.3783	336.0	570.0	0.5895	307.0	0.5386	124.0	128.0	158.0	0.8101	0.7848	93.0	98.0	152.0	0.6447	0.6118	62.0	77.0	142.0	0.5423	0.4366	28.0	33.0	118.0	0.2797	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	17.0	17	3.8947	0.0061	3202.7656	2219.9880	337.0	570.0	0.5912	309.0	0.5421	124.0	129.0	158.0	0.8165	0.7848	94.0	98.0	152.0	0.6447	0.6184	64.0	77.0	142.0	0.5423	0.4507	27.0	33.0	118.0	0.2797	0.2288	0.0	0.0	0.0	0.0	0.0
0.0	18.0	18	3.9091	0.0061	3214.5717	2228.1713	336.0	570.0	0.5895	307.0	0.5386	124.0	129.0	158.0	0.8165	0.7848	94.0	98.0	152.0	0.6447	0.6184	63.0	77.0	142.0	0.5423	0.4437	26.0	32.0	118.0	0.2712	0.2203	0.0	0.0	0.0	0.0	0.0
0.0	19.0	19	3.9319	0.0061	3233.3715	2241.2023	338.0	570.0	0.5930	312.0	0.5474	124.0	130.0	158.0	0.8228	0.7848	94.0	98.0	152.0	0.6447	0.6184	67.0	78.0	142.0	0.5493	0.4718	27.0	32.0	118.0	0.2712	0.2288	0.0	0.0	0.0	0.0	0.0
0.0	20.0	20	3.9430	0.0061	3242.4962	2247.5271	338.0	570.0	0.5930	312.0	0.5474	124.0	130.0	158.0	0.8228	0.7848	95.0	98.0	152.0	0.6447	0.625	64.0	76.0	142.0	0.5352	0.4507	29.0	34.0	118.0	0.2881	0.2458	0.0	0.0	0.0	0.0	0.0
0.0	21.0	21	3.9561	0.0061	3253.2053	2254.9501	335.0	570.0	0.5877	311.0	0.5456	125.0	130.0	158.0	0.8228	0.7911	95.0	98.0	152.0	0.6447	0.625	64.0	75.0	142.0	0.5282	0.4507	27.0	32.0	118.0	0.2712	0.2288	0.0	0.0	0.0	0.0	0.0
0.0	22.0	22	3.9402	0.0061	3240.1303	2245.8872	341.0	570.0	0.5982	314.0	0.5509	127.0	133.0	158.0	0.8418	0.8038	94.0	97.0	152.0	0.6382	0.6184	66.0	78.0	142.0	0.5493	0.4648	27.0	33.0	118.0	0.2797	0.2288	0.0	0.0	0.0	0.0	0.0
0.0	23.0	23	3.9841	0.0061	3276.2708	2270.9379	337.0	570.0	0.5912	309.0	0.5421	123.0	131.0	158.0	0.8291	0.7785	93.0	97.0	152.0	0.6382	0.6118	65.0	76.0	142.0	0.5352	0.4577	28.0	33.0	118.0	0.2797	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	24.0	24	3.9801	0.0061	3272.9577	2268.6414	341.0	570.0	0.5982	314.0	0.5509	126.0	132.0	158.0	0.8354	0.7975	93.0	97.0	152.0	0.6382	0.6118	65.0	78.0	142.0	0.5493	0.4577	30.0	34.0	118.0	0.2881	0.2542	0.0	0.0	0.0	0.0	0.0
0.0	25.0	25	3.9653	0.0061	3260.8094	2260.2208	336.0	570.0	0.5895	308.0	0.5404	123.0	131.0	158.0	0.8291	0.7785	94.0	97.0	152.0	0.6382	0.6184	64.0	75.0	142.0	0.5282	0.4507	27.0	33.0	118.0	0.2797	0.2288	0.0	0.0	0.0	0.0	0.0
0.0	26.0	26	3.9697	0.0061	3264.4225	2262.7253	339.0	570.0	0.5947	312.0	0.5474	126.0	133.0	158.0	0.8418	0.7975	94.0	98.0	152.0	0.6447	0.6184	63.0	74.0	142.0	0.5211	0.4437	29.0	34.0	118.0	0.2881	0.2458	0.0	0.0	0.0	0.0	0.0
0.0	27.0	27	3.9600	0.0061	3256.4563	2257.2035	340.0	570.0	0.5965	312.0	0.5474	122.0	129.0	158.0	0.8165	0.7722	94.0	98.0	152.0	0.6447	0.6184	67.0	79.0	142.0	0.5563	0.4718	29.0	34.0	118.0	0.2881	0.2458	0.0	0.0	0.0	0.0	0.0
0.0	28.0	28	3.9808	0.0061	3273.5887	2269.0788	340.0	570.0	0.5965	312.0	0.5474	125.0	132.0	158.0	0.8354	0.7911	94.0	98.0	152.0	0.6447	0.6184	65.0	76.0	142.0	0.5352	0.4577	28.0	34.0	118.0	0.2881	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	29.0	29	3.9802	0.0061	3273.0894	2268.7327	335.0	570.0	0.5877	307.0	0.5386	124.0	132.0	158.0	0.8354	0.7848	93.0	97.0	152.0	0.6382	0.6118	63.0	74.0	142.0	0.5211	0.4437	27.0	32.0	118.0	0.2712	0.2288	0.0	0.0	0.0	0.0	0.0
0.0	30.0	30	3.9740	0.0061	3267.9798	2265.1910	338.0	570.0	0.5930	309.0	0.5421	124.0	130.0	158.0	0.8228	0.7848	94.0	98.0	152.0	0.6447	0.6184	65.0	77.0	142.0	0.5423	0.4577	26.0	33.0	118.0	0.2797	0.2203	0.0	0.0	0.0	0.0	0.0
0.0	31.0	31	3.9859	0.0061	3277.7667	2271.9748	339.0	570.0	0.5947	310.0	0.5439	123.0	131.0	158.0	0.8291	0.7785	94.0	98.0	152.0	0.6447	0.6184	65.0	76.0	142.0	0.5352	0.4577	28.0	34.0	118.0	0.2881	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	32.0	32	3.9724	0.0061	3266.6221	2264.2499	339.0	570.0	0.5947	310.0	0.5439	124.0	131.0	158.0	0.8291	0.7848	93.0	97.0	152.0	0.6382	0.6118	65.0	77.0	142.0	0.5423	0.4577	28.0	34.0	118.0	0.2881	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	33.0	33	3.9885	0.0061	3279.8737	2273.4352	340.0	570.0	0.5965	309.0	0.5421	124.0	131.0	158.0	0.8291	0.7848	93.0	97.0	152.0	0.6382	0.6118	66.0	79.0	142.0	0.5563	0.4648	26.0	33.0	118.0	0.2797	0.2203	0.0	0.0	0.0	0.0	0.0
0.0	34.0	34	3.9903	0.0061	3281.3424	2274.4533	339.0	570.0	0.5947	313.0	0.5491	124.0	130.0	158.0	0.8228	0.7848	94.0	98.0	152.0	0.6447	0.6184	66.0	77.0	142.0	0.5423	0.4648	29.0	34.0	118.0	0.2881	0.2458	0.0	0.0	0.0	0.0	0.0
0.0	35.0	35	3.9920	0.0061	3282.7598	2275.4357	339.0	570.0	0.5947	311.0	0.5456	124.0	131.0	158.0	0.8291	0.7848	94.0	98.0	152.0	0.6447	0.6184	65.0	77.0	142.0	0.5423	0.4577	28.0	33.0	118.0	0.2797	0.2373	0.0	0.0	0.0	0.0	0.0
0.0	36.0	36	3.9818	0.0061	3274.3896	2269.6339	339.0	570.0	0.5947	310.0	0.5439	123.0	131.0	158.0	0.8291	0.7785	93.0	97.0	152.0	0.6382	0.6118	66.0	78.0	142.0	0.5493	0.4648	28.0	33.0	118.0	0.2797	0.2373	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