ARC-Easy_Llama-3.2-1B-yn0mux6w

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: 2.7219
• Model Preparation Time: 0.0062
• Mdl: 2238.3307
• Accumulated Loss: 1551.4926
• Correct Preds: 386.0
• Total Preds: 570.0
• Accuracy: 0.6772
• Correct Gen Preds: 367.0
• Gen Accuracy: 0.6439
• Correct Gen Preds 32: 95.0
• Correct Preds 32: 106.0
• Total Labels 32: 158.0
• Accuracy 32: 0.6709
• Gen Accuracy 32: 0.6013
• Correct Gen Preds 33: 101.0
• Correct Preds 33: 103.0
• Total Labels 33: 152.0
• Accuracy 33: 0.6776
• Gen Accuracy 33: 0.6645
• Correct Gen Preds 34: 102.0
• Correct Preds 34: 106.0
• Total Labels 34: 142.0
• Accuracy 34: 0.7465
• Gen Accuracy 34: 0.7183
• Correct Gen Preds 35: 69.0
• Correct Preds 35: 71.0
• Total Labels 35: 118.0
• Accuracy 35: 0.6017
• Gen Accuracy 35: 0.5847
• 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	0.0062	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
1.3774	1.0	1	1.5354	0.0062	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
1.3774	2.0	2	2.5968	0.0062	2135.4404	1480.1745	155.0	570.0	0.2719	155.0	0.2719	0.0	0.0	158.0	0.0	0.0	152.0	152.0	152.0	1.0	1.0	3.0	3.0	142.0	0.0211	0.0211	0.0	0.0	118.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.9382	3.0	3	1.6496	0.0062	1356.5201	940.2681	222.0	570.0	0.3895	222.0	0.3895	109.0	109.0	158.0	0.6899	0.6899	112.0	112.0	152.0	0.7368	0.7368	1.0	1.0	142.0	0.0070	0.0070	0.0	0.0	118.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.6757	4.0	4	1.5680	0.0062	1289.4396	893.7715	264.0	570.0	0.4632	263.0	0.4614	146.0	147.0	158.0	0.9304	0.9241	20.0	20.0	152.0	0.1316	0.1316	70.0	70.0	142.0	0.4930	0.4930	27.0	27.0	118.0	0.2288	0.2288	0.0	0.0	0.0	0.0	0.0
0.2038	5.0	5	1.2887	0.0062	1059.7154	734.5388	383.0	570.0	0.6719	374.0	0.6561	104.0	108.0	158.0	0.6835	0.6582	93.0	96.0	152.0	0.6316	0.6118	108.0	108.0	142.0	0.7606	0.7606	69.0	71.0	118.0	0.6017	0.5847	0.0	0.0	0.0	0.0	0.0
0.0105	6.0	6	2.0876	0.0062	1716.6885	1189.9178	384.0	570.0	0.6737	369.0	0.6474	95.0	105.0	158.0	0.6646	0.6013	100.0	102.0	152.0	0.6711	0.6579	104.0	106.0	142.0	0.7465	0.7324	70.0	71.0	118.0	0.6017	0.5932	0.0	0.0	0.0	0.0	0.0
0.0	7.0	7	2.7219	0.0062	2238.3307	1551.4926	386.0	570.0	0.6772	367.0	0.6439	95.0	106.0	158.0	0.6709	0.6013	101.0	103.0	152.0	0.6776	0.6645	102.0	106.0	142.0	0.7465	0.7183	69.0	71.0	118.0	0.6017	0.5847	0.0	0.0	0.0	0.0	0.0
0.0	8.0	8	3.1286	0.0062	2572.7573	1783.2995	386.0	570.0	0.6772	365.0	0.6404	94.0	104.0	158.0	0.6582	0.5949	104.0	107.0	152.0	0.7039	0.6842	99.0	104.0	142.0	0.7324	0.6972	68.0	71.0	118.0	0.6017	0.5763	0.0	0.0	0.0	0.0	0.0
0.0	9.0	9	3.4176	0.0062	2810.4409	1948.0492	383.0	570.0	0.6719	357.0	0.6263	86.0	101.0	158.0	0.6392	0.5443	104.0	107.0	152.0	0.7039	0.6842	98.0	103.0	142.0	0.7254	0.6901	69.0	72.0	118.0	0.6102	0.5847	0.0	0.0	0.0	0.0	0.0
0.0	10.0	10	3.5967	0.0062	2957.6771	2050.1055	386.0	570.0	0.6772	356.0	0.6246	82.0	101.0	158.0	0.6392	0.5190	107.0	109.0	152.0	0.7171	0.7039	100.0	105.0	142.0	0.7394	0.7042	67.0	71.0	118.0	0.6017	0.5678	0.0	0.0	0.0	0.0	0.0
0.0	11.0	11	3.7561	0.0062	3088.7869	2140.9839	380.0	570.0	0.6667	350.0	0.6140	79.0	98.0	158.0	0.6203	0.5	106.0	108.0	152.0	0.7105	0.6974	99.0	104.0	142.0	0.7324	0.6972	66.0	70.0	118.0	0.5932	0.5593	0.0	0.0	0.0	0.0	0.0
0.0	12.0	12	3.8571	0.0062	3171.8705	2198.5731	379.0	570.0	0.6649	347.0	0.6088	76.0	97.0	158.0	0.6139	0.4810	106.0	108.0	152.0	0.7105	0.6974	99.0	105.0	142.0	0.7394	0.6972	66.0	69.0	118.0	0.5847	0.5593	0.0	0.0	0.0	0.0	0.0
0.0	13.0	13	3.9345	0.0062	3235.4696	2242.6566	378.0	570.0	0.6632	348.0	0.6105	77.0	95.0	158.0	0.6013	0.4873	106.0	109.0	152.0	0.7171	0.6974	99.0	105.0	142.0	0.7394	0.6972	66.0	69.0	118.0	0.5847	0.5593	0.0	0.0	0.0	0.0	0.0
0.0	14.0	14	3.9977	0.0062	3287.4322	2278.6744	378.0	570.0	0.6632	345.0	0.6053	75.0	96.0	158.0	0.6076	0.4747	106.0	108.0	152.0	0.7105	0.6974	99.0	105.0	142.0	0.7394	0.6972	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	15.0	15	4.0354	0.0062	3318.4791	2300.1944	379.0	570.0	0.6649	345.0	0.6053	76.0	96.0	158.0	0.6076	0.4810	107.0	109.0	152.0	0.7171	0.7039	97.0	105.0	142.0	0.7394	0.6831	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	16.0	16	4.0486	0.0062	3329.3097	2307.7017	375.0	570.0	0.6579	339.0	0.5947	72.0	96.0	158.0	0.6076	0.4557	107.0	109.0	152.0	0.7171	0.7039	95.0	101.0	142.0	0.7113	0.6690	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	17.0	17	4.1223	0.0062	3389.9024	2349.7013	376.0	570.0	0.6596	340.0	0.5965	72.0	96.0	158.0	0.6076	0.4557	106.0	109.0	152.0	0.7171	0.6974	96.0	102.0	142.0	0.7183	0.6761	66.0	69.0	118.0	0.5847	0.5593	0.0	0.0	0.0	0.0	0.0
0.0	18.0	18	4.0992	0.0062	3370.9264	2336.5481	375.0	570.0	0.6579	338.0	0.5930	72.0	96.0	158.0	0.6076	0.4557	105.0	108.0	152.0	0.7105	0.6908	97.0	103.0	142.0	0.7254	0.6831	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	19.0	19	4.1257	0.0062	3392.7407	2351.6686	378.0	570.0	0.6632	340.0	0.5965	71.0	95.0	158.0	0.6013	0.4494	107.0	109.0	152.0	0.7171	0.7039	97.0	105.0	142.0	0.7394	0.6831	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	20.0	20	4.1234	0.0062	3390.8098	2350.3302	378.0	570.0	0.6632	339.0	0.5947	70.0	96.0	158.0	0.6076	0.4430	107.0	109.0	152.0	0.7171	0.7039	97.0	104.0	142.0	0.7324	0.6831	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	21.0	21	4.1404	0.0062	3404.8216	2360.0425	376.0	570.0	0.6596	338.0	0.5930	71.0	96.0	158.0	0.6076	0.4494	107.0	109.0	152.0	0.7171	0.7039	96.0	103.0	142.0	0.7254	0.6761	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	22.0	22	4.1645	0.0062	3424.6124	2373.7604	376.0	570.0	0.6596	339.0	0.5947	70.0	95.0	158.0	0.6013	0.4430	108.0	109.0	152.0	0.7171	0.7105	96.0	103.0	142.0	0.7254	0.6761	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	23.0	23	4.1592	0.0062	3420.2355	2370.7266	379.0	570.0	0.6649	341.0	0.5982	71.0	96.0	158.0	0.6076	0.4494	106.0	109.0	152.0	0.7171	0.6974	98.0	105.0	142.0	0.7394	0.6901	66.0	69.0	118.0	0.5847	0.5593	0.0	0.0	0.0	0.0	0.0
0.0	24.0	24	4.1565	0.0062	3418.0247	2369.1942	378.0	570.0	0.6632	340.0	0.5965	70.0	96.0	158.0	0.6076	0.4430	107.0	109.0	152.0	0.7171	0.7039	99.0	105.0	142.0	0.7394	0.6972	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	25.0	25	4.1931	0.0062	3448.1315	2390.0626	376.0	570.0	0.6596	341.0	0.5982	70.0	95.0	158.0	0.6013	0.4430	107.0	108.0	152.0	0.7105	0.7039	99.0	104.0	142.0	0.7324	0.6972	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	26.0	26	4.1936	0.0062	3448.5798	2390.3734	372.0	570.0	0.6526	336.0	0.5895	71.0	95.0	158.0	0.6013	0.4494	105.0	108.0	152.0	0.7105	0.6908	96.0	101.0	142.0	0.7113	0.6761	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	27.0	27	4.1744	0.0062	3432.7320	2379.3885	376.0	570.0	0.6596	338.0	0.5930	70.0	96.0	158.0	0.6076	0.4430	106.0	108.0	152.0	0.7105	0.6974	98.0	104.0	142.0	0.7324	0.6901	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	28.0	28	4.1920	0.0062	3447.2556	2389.4555	378.0	570.0	0.6632	341.0	0.5982	71.0	96.0	158.0	0.6076	0.4494	107.0	109.0	152.0	0.7171	0.7039	98.0	104.0	142.0	0.7324	0.6901	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	29.0	29	4.1905	0.0062	3446.0259	2388.6031	376.0	570.0	0.6596	339.0	0.5947	70.0	96.0	158.0	0.6076	0.4430	106.0	108.0	152.0	0.7105	0.6974	99.0	105.0	142.0	0.7394	0.6972	64.0	67.0	118.0	0.5678	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	30.0	30	4.1922	0.0062	3447.3786	2389.5408	377.0	570.0	0.6614	339.0	0.5947	70.0	95.0	158.0	0.6013	0.4430	106.0	109.0	152.0	0.7171	0.6974	99.0	104.0	142.0	0.7324	0.6972	64.0	69.0	118.0	0.5847	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	31.0	31	4.1992	0.0062	3453.1486	2393.5402	378.0	570.0	0.6632	339.0	0.5947	70.0	96.0	158.0	0.6076	0.4430	106.0	108.0	152.0	0.7105	0.6974	98.0	105.0	142.0	0.7394	0.6901	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	32.0	32	4.1634	0.0062	3423.6761	2373.1115	373.0	570.0	0.6544	338.0	0.5930	69.0	94.0	158.0	0.5949	0.4367	107.0	108.0	152.0	0.7105	0.7039	98.0	103.0	142.0	0.7254	0.6901	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	33.0	33	4.1932	0.0062	3448.1967	2390.1078	376.0	570.0	0.6596	338.0	0.5930	70.0	95.0	158.0	0.6013	0.4430	106.0	109.0	152.0	0.7171	0.6974	97.0	103.0	142.0	0.7254	0.6831	65.0	69.0	118.0	0.5847	0.5508	0.0	0.0	0.0	0.0	0.0
0.0	34.0	34	4.2044	0.0062	3457.3908	2396.4807	376.0	570.0	0.6596	340.0	0.5965	70.0	95.0	158.0	0.6013	0.4430	107.0	108.0	152.0	0.7105	0.7039	99.0	105.0	142.0	0.7394	0.6972	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	35.0	35	4.1960	0.0062	3450.5312	2391.7260	376.0	570.0	0.6596	340.0	0.5965	71.0	95.0	158.0	0.6013	0.4494	106.0	109.0	152.0	0.7171	0.6974	99.0	104.0	142.0	0.7324	0.6972	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	36.0	36	4.2146	0.0062	3465.8272	2402.3283	376.0	570.0	0.6596	338.0	0.5930	70.0	94.0	158.0	0.5949	0.4430	106.0	109.0	152.0	0.7171	0.6974	98.0	105.0	142.0	0.7394	0.6901	64.0	68.0	118.0	0.5763	0.5424	0.0	0.0	0.0	0.0	0.0
0.0	37.0	37	4.2056	0.0062	3458.4119	2397.1884	374.0	570.0	0.6561	334.0	0.5860	69.0	94.0	158.0	0.5949	0.4367	105.0	108.0	152.0	0.7105	0.6908	96.0	104.0	142.0	0.7324	0.6761	64.0	68.0	118.0	0.5763	0.5424	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