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ARC-Easy_Llama-3.2-1B-eecazfmn

Text Generation
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llama
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text-generation-inference
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ARC-Easy_Llama-3.2-1B-eecazfmn

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: 2.3773
  • Model Preparation Time: 0.0057
  • Mdl: 1954.8994
  • Accumulated Loss: 1355.0330
  • Correct Preds: 356.0
  • Total Preds: 570.0
  • Accuracy: 0.6246
  • Correct Gen Preds: 351.0
  • Gen Accuracy: 0.6158
  • Correct Gen Preds 32: 124.0
  • Correct Preds 32: 125.0
  • Total Labels 32: 158.0
  • Accuracy 32: 0.7911
  • Gen Accuracy 32: 0.7848
  • Correct Gen Preds 33: 107.0
  • Correct Preds 33: 109.0
  • Total Labels 33: 152.0
  • Accuracy 33: 0.7171
  • Gen Accuracy 33: 0.7039
  • Correct Gen Preds 34: 79.0
  • Correct Preds 34: 81.0
  • Total Labels 34: 142.0
  • Accuracy 34: 0.5704
  • Gen Accuracy 34: 0.5563
  • Correct Gen Preds 35: 41.0
  • Correct Preds 35: 41.0
  • Total Labels 35: 118.0
  • Accuracy 35: 0.3475
  • Gen Accuracy 35: 0.3475
  • 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 0.0057 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
1.3531 1.0 1 1.5354 0.0057 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
1.3531 2.0 2 2.3144 0.0057 1903.2267 1319.2162 152.0 570.0 0.2667 152.0 0.2667 0.0 0.0 158.0 0.0 0.0 152.0 152.0 152.0 1.0 1.0 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
1.8233 3.0 3 1.4965 0.0057 1230.6575 853.0268 159.0 570.0 0.2789 159.0 0.2789 158.0 158.0 158.0 1.0 1.0 0.0 0.0 152.0 0.0 0.0 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
0.8791 4.0 4 1.0754 0.0057 884.3810 613.0062 307.0 570.0 0.5386 307.0 0.5386 114.0 114.0 158.0 0.7215 0.7215 11.0 11.0 152.0 0.0724 0.0724 98.0 98.0 142.0 0.6901 0.6901 84.0 84.0 118.0 0.7119 0.7119 0.0 0.0 0.0 0.0 0.0
0.4849 5.0 5 1.9580 0.0057 1610.1108 1116.0437 292.0 570.0 0.5123 292.0 0.5123 149.0 149.0 158.0 0.9430 0.9430 30.0 30.0 152.0 0.1974 0.1974 66.0 66.0 142.0 0.4648 0.4648 47.0 47.0 118.0 0.3983 0.3983 0.0 0.0 0.0 0.0 0.0
0.2217 6.0 6 1.7848 0.0057 1467.6739 1017.3141 339.0 570.0 0.5947 296.0 0.5193 98.0 116.0 158.0 0.7342 0.6203 95.0 110.0 152.0 0.7237 0.625 65.0 74.0 142.0 0.5211 0.4577 38.0 39.0 118.0 0.3305 0.3220 0.0 0.0 0.0 0.0 0.0
0.0696 7.0 7 2.3773 0.0057 1954.8994 1355.0330 356.0 570.0 0.6246 351.0 0.6158 124.0 125.0 158.0 0.7911 0.7848 107.0 109.0 152.0 0.7171 0.7039 79.0 81.0 142.0 0.5704 0.5563 41.0 41.0 118.0 0.3475 0.3475 0.0 0.0 0.0 0.0 0.0
0.0037 8.0 8 4.1178 0.0057 3386.1975 2347.1332 351.0 570.0 0.6158 351.0 0.6158 137.0 137.0 158.0 0.8671 0.8671 100.0 100.0 152.0 0.6579 0.6579 73.0 73.0 142.0 0.5141 0.5141 41.0 41.0 118.0 0.3475 0.3475 0.0 0.0 0.0 0.0 0.0
0.0 9.0 9 5.4025 0.0057 4442.6583 3079.4161 336.0 570.0 0.5895 331.0 0.5807 133.0 138.0 158.0 0.8734 0.8418 92.0 92.0 152.0 0.6053 0.6053 67.0 67.0 142.0 0.4718 0.4718 39.0 39.0 118.0 0.3305 0.3305 0.0 0.0 0.0 0.0 0.0
0.0 10.0 10 6.2570 0.0057 5145.3854 3566.5094 330.0 570.0 0.5789 315.0 0.5526 126.0 141.0 158.0 0.8924 0.7975 92.0 92.0 152.0 0.6053 0.6053 64.0 64.0 142.0 0.4507 0.4507 33.0 33.0 118.0 0.2797 0.2797 0.0 0.0 0.0 0.0 0.0
0.0 11.0 11 6.8353 0.0057 5620.9324 3896.1334 329.0 570.0 0.5772 314.0 0.5509 128.0 143.0 158.0 0.9051 0.8101 91.0 91.0 152.0 0.5987 0.5987 62.0 62.0 142.0 0.4366 0.4366 33.0 33.0 118.0 0.2797 0.2797 0.0 0.0 0.0 0.0 0.0
0.0 12.0 12 7.2254 0.0057 5941.6769 4118.4566 326.0 570.0 0.5719 314.0 0.5509 131.0 143.0 158.0 0.9051 0.8291 91.0 91.0 152.0 0.5987 0.5987 59.0 59.0 142.0 0.4155 0.4155 33.0 33.0 118.0 0.2797 0.2797 0.0 0.0 0.0 0.0 0.0
0.0 13.0 13 7.4730 0.0057 6145.3165 4259.6088 322.0 570.0 0.5649 312.0 0.5474 134.0 144.0 158.0 0.9114 0.8481 91.0 91.0 152.0 0.5987 0.5987 55.0 55.0 142.0 0.3873 0.3873 32.0 32.0 118.0 0.2712 0.2712 0.0 0.0 0.0 0.0 0.0
0.0 14.0 14 7.6164 0.0057 6263.2805 4341.3752 321.0 570.0 0.5632 313.0 0.5491 137.0 145.0 158.0 0.9177 0.8671 89.0 89.0 152.0 0.5855 0.5855 55.0 55.0 142.0 0.3873 0.3873 32.0 32.0 118.0 0.2712 0.2712 0.0 0.0 0.0 0.0 0.0
0.0 15.0 15 7.7243 0.0057 6351.9819 4402.8583 318.0 570.0 0.5579 313.0 0.5491 140.0 145.0 158.0 0.9177 0.8861 88.0 88.0 152.0 0.5789 0.5789 53.0 53.0 142.0 0.3732 0.3732 32.0 32.0 118.0 0.2712 0.2712 0.0 0.0 0.0 0.0 0.0
0.0 16.0 16 7.7785 0.0057 6396.5780 4433.7700 317.0 570.0 0.5561 313.0 0.5491 141.0 145.0 158.0 0.9177 0.8924 87.0 87.0 152.0 0.5724 0.5724 53.0 53.0 142.0 0.3732 0.3732 32.0 32.0 118.0 0.2712 0.2712 0.0 0.0 0.0 0.0 0.0
0.0 17.0 17 7.8645 0.0057 6467.2957 4482.7878 315.0 570.0 0.5526 312.0 0.5474 142.0 145.0 158.0 0.9177 0.8987 88.0 88.0 152.0 0.5789 0.5789 51.0 51.0 142.0 0.3592 0.3592 31.0 31.0 118.0 0.2627 0.2627 0.0 0.0 0.0 0.0 0.0
0.0 18.0 18 7.9027 0.0057 6498.6900 4504.5487 316.0 570.0 0.5544 312.0 0.5474 141.0 145.0 158.0 0.9177 0.8924 87.0 87.0 152.0 0.5724 0.5724 53.0 53.0 142.0 0.3732 0.3732 31.0 31.0 118.0 0.2627 0.2627 0.0 0.0 0.0 0.0 0.0
0.0 19.0 19 7.9998 0.0057 6578.5635 4559.9128 313.0 570.0 0.5491 310.0 0.5439 142.0 145.0 158.0 0.9177 0.8987 86.0 86.0 152.0 0.5658 0.5658 52.0 52.0 142.0 0.3662 0.3662 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 20.0 20 8.0042 0.0057 6582.1226 4562.3797 314.0 570.0 0.5509 311.0 0.5456 142.0 145.0 158.0 0.9177 0.8987 85.0 85.0 152.0 0.5592 0.5592 54.0 54.0 142.0 0.3803 0.3803 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 21.0 21 8.0503 0.0057 6620.0897 4588.6965 311.0 570.0 0.5456 308.0 0.5404 142.0 145.0 158.0 0.9177 0.8987 84.0 84.0 152.0 0.5526 0.5526 52.0 52.0 142.0 0.3662 0.3662 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 22.0 22 8.0228 0.0057 6597.4578 4573.0092 315.0 570.0 0.5526 313.0 0.5491 143.0 145.0 158.0 0.9177 0.9051 85.0 85.0 152.0 0.5592 0.5592 53.0 53.0 142.0 0.3732 0.3732 32.0 32.0 118.0 0.2712 0.2712 0.0 0.0 0.0 0.0 0.0
0.0 23.0 23 8.1360 0.0057 6690.5589 4637.5420 312.0 570.0 0.5474 309.0 0.5421 142.0 145.0 158.0 0.9177 0.8987 85.0 85.0 152.0 0.5592 0.5592 52.0 52.0 142.0 0.3662 0.3662 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 24.0 24 8.1110 0.0057 6669.9872 4623.2829 315.0 570.0 0.5526 314.0 0.5509 145.0 146.0 158.0 0.9241 0.9177 85.0 85.0 152.0 0.5592 0.5592 54.0 54.0 142.0 0.3803 0.3803 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 25.0 25 8.0899 0.0057 6652.6387 4611.2577 313.0 570.0 0.5491 312.0 0.5474 145.0 146.0 158.0 0.9241 0.9177 83.0 83.0 152.0 0.5461 0.5461 54.0 54.0 142.0 0.3803 0.3803 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 26.0 26 8.0958 0.0057 6657.4563 4614.5971 315.0 570.0 0.5526 313.0 0.5491 143.0 145.0 158.0 0.9177 0.9051 83.0 83.0 152.0 0.5461 0.5461 55.0 55.0 142.0 0.3873 0.3873 32.0 32.0 118.0 0.2712 0.2712 0.0 0.0 0.0 0.0 0.0
0.0 27.0 27 8.1194 0.0057 6676.9034 4628.0768 314.0 570.0 0.5509 312.0 0.5474 143.0 145.0 158.0 0.9177 0.9051 85.0 85.0 152.0 0.5592 0.5592 54.0 54.0 142.0 0.3803 0.3803 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 28.0 28 8.1511 0.0057 6702.9764 4646.1492 314.0 570.0 0.5509 313.0 0.5491 144.0 145.0 158.0 0.9177 0.9114 84.0 84.0 152.0 0.5526 0.5526 55.0 55.0 142.0 0.3873 0.3873 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 29.0 29 8.1586 0.0057 6709.1201 4650.4077 313.0 570.0 0.5491 313.0 0.5491 145.0 145.0 158.0 0.9177 0.9177 83.0 83.0 152.0 0.5461 0.5461 54.0 54.0 142.0 0.3803 0.3803 31.0 31.0 118.0 0.2627 0.2627 0.0 0.0 0.0 0.0 0.0
0.0 30.0 30 8.1033 0.0057 6663.6069 4618.8603 312.0 570.0 0.5474 310.0 0.5439 143.0 145.0 158.0 0.9177 0.9051 84.0 84.0 152.0 0.5526 0.5526 53.0 53.0 142.0 0.3732 0.3732 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 31.0 31 8.1388 0.0057 6692.8394 4639.1227 317.0 570.0 0.5561 316.0 0.5544 144.0 145.0 158.0 0.9177 0.9114 85.0 85.0 152.0 0.5592 0.5592 56.0 56.0 142.0 0.3944 0.3944 31.0 31.0 118.0 0.2627 0.2627 0.0 0.0 0.0 0.0 0.0
0.0 32.0 32 8.1790 0.0057 6725.8530 4662.0061 312.0 570.0 0.5474 311.0 0.5456 144.0 145.0 158.0 0.9177 0.9114 83.0 83.0 152.0 0.5461 0.5461 53.0 53.0 142.0 0.3732 0.3732 31.0 31.0 118.0 0.2627 0.2627 0.0 0.0 0.0 0.0 0.0
0.0 33.0 33 8.1788 0.0057 6725.7129 4661.9089 314.0 570.0 0.5509 314.0 0.5509 145.0 145.0 158.0 0.9177 0.9177 83.0 83.0 152.0 0.5461 0.5461 56.0 56.0 142.0 0.3944 0.3944 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 34.0 34 8.1461 0.0057 6698.7991 4643.2537 315.0 570.0 0.5526 315.0 0.5526 145.0 145.0 158.0 0.9177 0.9177 84.0 84.0 152.0 0.5526 0.5526 56.0 56.0 142.0 0.3944 0.3944 30.0 30.0 118.0 0.2542 0.2542 0.0 0.0 0.0 0.0 0.0
0.0 35.0 35 8.1543 0.0057 6705.5694 4647.9465 315.0 570.0 0.5526 314.0 0.5509 144.0 145.0 158.0 0.9177 0.9114 85.0 85.0 152.0 0.5592 0.5592 54.0 54.0 142.0 0.3803 0.3803 31.0 31.0 118.0 0.2627 0.2627 0.0 0.0 0.0 0.0 0.0
0.0 36.0 36 8.1585 0.0057 6709.0706 4650.3734 315.0 570.0 0.5526 315.0 0.5526 145.0 145.0 158.0 0.9177 0.9177 83.0 83.0 152.0 0.5461 0.5461 56.0 56.0 142.0 0.3944 0.3944 31.0 31.0 118.0 0.2627 0.2627 0.0 0.0 0.0 0.0 0.0
0.0 37.0 37 8.1496 0.0057 6701.7266 4645.2829 314.0 570.0 0.5509 313.0 0.5491 144.0 145.0 158.0 0.9177 0.9114 85.0 85.0 152.0 0.5592 0.5592 55.0 55.0 142.0 0.3873 0.3873 29.0 29.0 118.0 0.2458 0.2458 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
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