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ARC-Challenge_Llama-3.2-1B-5isumep7

Text Generation
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llama
Generated from Trainer
text-generation-inference
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ARC-Challenge_Llama-3.2-1B-5isumep7

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: 7.8009
  • Model Preparation Time: 0.0058
  • Mdl: 3365.0442
  • Accumulated Loss: 2332.4709
  • Correct Preds: 106.0
  • Total Preds: 299.0
  • Accuracy: 0.3545
  • Correct Gen Preds: 88.0
  • Gen Accuracy: 0.2943
  • Correct Gen Preds 32: 0.0
  • Correct Preds 32: 1.0
  • Total Labels 32: 64.0
  • Accuracy 32: 0.0156
  • Gen Accuracy 32: 0.0
  • Correct Gen Preds 33: 28.0
  • Correct Preds 33: 33.0
  • Total Labels 33: 73.0
  • Accuracy 33: 0.4521
  • Gen Accuracy 33: 0.3836
  • Correct Gen Preds 34: 42.0
  • Correct Preds 34: 47.0
  • Total Labels 34: 78.0
  • Accuracy 34: 0.6026
  • Gen Accuracy 34: 0.5385
  • Correct Gen Preds 35: 18.0
  • Correct Preds 35: 25.0
  • Total Labels 35: 83.0
  • Accuracy 35: 0.3012
  • Gen Accuracy 35: 0.2169
  • Correct Gen Preds 36: 0.0
  • Correct Preds 36: 0.0
  • Total Labels 36: 1.0
  • 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 1.6389 0.0058 706.9523 490.0220 66.0 299.0 0.2207 66.0 0.2207 62.0 62.0 64.0 0.9688 0.9688 0.0 0.0 73.0 0.0 0.0 4.0 4.0 78.0 0.0513 0.0513 0.0 0.0 83.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0
1.7995 1.0 1 1.6389 0.0058 706.9523 490.0220 66.0 299.0 0.2207 66.0 0.2207 62.0 62.0 64.0 0.9688 0.9688 0.0 0.0 73.0 0.0 0.0 4.0 4.0 78.0 0.0513 0.0513 0.0 0.0 83.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0
1.7995 2.0 2 2.2937 0.0058 989.4309 685.8212 80.0 299.0 0.2676 80.0 0.2676 0.0 0.0 64.0 0.0 0.0 71.0 71.0 73.0 0.9726 0.9726 9.0 9.0 78.0 0.1154 0.1154 0.0 0.0 83.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0
1.267 3.0 3 1.6015 0.0058 690.8479 478.8593 89.0 299.0 0.2977 89.0 0.2977 0.0 0.0 64.0 0.0 0.0 9.0 9.0 73.0 0.1233 0.1233 4.0 4.0 78.0 0.0513 0.0513 76.0 76.0 83.0 0.9157 0.9157 0.0 0.0 1.0 0.0 0.0
0.8933 4.0 4 1.6894 0.0058 728.7577 505.1363 82.0 299.0 0.2742 76.0 0.2542 0.0 1.0 64.0 0.0156 0.0 60.0 64.0 73.0 0.8767 0.8219 14.0 15.0 78.0 0.1923 0.1795 2.0 2.0 83.0 0.0241 0.0241 0.0 0.0 1.0 0.0 0.0
0.2132 5.0 5 2.5134 0.0058 1084.1873 751.5014 82.0 299.0 0.2742 68.0 0.2274 0.0 2.0 64.0 0.0312 0.0 47.0 57.0 73.0 0.7808 0.6438 17.0 18.0 78.0 0.2308 0.2179 4.0 5.0 83.0 0.0602 0.0482 0.0 0.0 1.0 0.0 0.0
0.0162 6.0 6 3.6396 0.0058 1569.9815 1088.2283 86.0 299.0 0.2876 42.0 0.1405 0.0 4.0 64.0 0.0625 0.0 18.0 46.0 73.0 0.6301 0.2466 18.0 26.0 78.0 0.3333 0.2308 6.0 10.0 83.0 0.1205 0.0723 0.0 0.0 1.0 0.0 0.0
0.0003 7.0 7 4.5675 0.0058 1970.2637 1365.6827 93.0 299.0 0.3110 59.0 0.1973 0.0 2.0 64.0 0.0312 0.0 26.0 48.0 73.0 0.6575 0.3562 25.0 30.0 78.0 0.3846 0.3205 8.0 13.0 83.0 0.1566 0.0964 0.0 0.0 1.0 0.0 0.0
0.0 8.0 8 5.2552 0.0058 2266.9178 1571.3076 100.0 299.0 0.3344 70.0 0.2341 0.0 1.0 64.0 0.0156 0.0 28.0 46.0 73.0 0.6301 0.3836 30.0 35.0 78.0 0.4487 0.3846 12.0 18.0 83.0 0.2169 0.1446 0.0 0.0 1.0 0.0 0.0
0.0 9.0 9 5.7907 0.0058 2497.9193 1731.4257 101.0 299.0 0.3378 69.0 0.2308 0.0 0.0 64.0 0.0 0.0 26.0 44.0 73.0 0.6027 0.3562 29.0 38.0 78.0 0.4872 0.3718 14.0 19.0 83.0 0.2289 0.1687 0.0 0.0 1.0 0.0 0.0
0.0 10.0 10 6.2295 0.0058 2687.1969 1862.6230 98.0 299.0 0.3278 71.0 0.2375 0.0 0.0 64.0 0.0 0.0 26.0 41.0 73.0 0.5616 0.3562 34.0 40.0 78.0 0.5128 0.4359 11.0 17.0 83.0 0.2048 0.1325 0.0 0.0 1.0 0.0 0.0
0.0 11.0 11 6.5743 0.0058 2835.9109 1965.7036 100.0 299.0 0.3344 76.0 0.2542 0.0 1.0 64.0 0.0156 0.0 27.0 39.0 73.0 0.5342 0.3699 36.0 41.0 78.0 0.5256 0.4615 13.0 19.0 83.0 0.2289 0.1566 0.0 0.0 1.0 0.0 0.0
0.0 12.0 12 6.8050 0.0058 2935.4320 2034.6864 104.0 299.0 0.3478 79.0 0.2642 0.0 1.0 64.0 0.0156 0.0 28.0 39.0 73.0 0.5342 0.3836 37.0 44.0 78.0 0.5641 0.4744 14.0 20.0 83.0 0.2410 0.1687 0.0 0.0 1.0 0.0 0.0
0.0 13.0 13 7.0095 0.0058 3023.6716 2095.8495 104.0 299.0 0.3478 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 28.0 39.0 73.0 0.5342 0.3836 39.0 44.0 78.0 0.5641 0.5 14.0 20.0 83.0 0.2410 0.1687 0.0 0.0 1.0 0.0 0.0
0.0 14.0 14 7.1582 0.0058 3087.7993 2140.2994 103.0 299.0 0.3445 80.0 0.2676 0.0 1.0 64.0 0.0156 0.0 28.0 36.0 73.0 0.4932 0.3836 39.0 45.0 78.0 0.5769 0.5 13.0 21.0 83.0 0.2530 0.1566 0.0 0.0 1.0 0.0 0.0
0.0 15.0 15 7.2819 0.0058 3141.1773 2177.2982 100.0 299.0 0.3344 78.0 0.2609 0.0 1.0 64.0 0.0156 0.0 27.0 35.0 73.0 0.4795 0.3699 39.0 45.0 78.0 0.5769 0.5 12.0 19.0 83.0 0.2289 0.1446 0.0 0.0 1.0 0.0 0.0
0.0 16.0 16 7.3814 0.0058 3184.0741 2207.0320 102.0 299.0 0.3411 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 27.0 34.0 73.0 0.4658 0.3699 39.0 45.0 78.0 0.5769 0.5 15.0 22.0 83.0 0.2651 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 17.0 17 7.5501 0.0058 3256.8522 2257.4779 100.0 299.0 0.3344 79.0 0.2642 0.0 1.0 64.0 0.0156 0.0 25.0 33.0 73.0 0.4521 0.3425 41.0 45.0 78.0 0.5769 0.5256 13.0 21.0 83.0 0.2530 0.1566 0.0 0.0 1.0 0.0 0.0
0.0 18.0 18 7.5594 0.0058 3260.8747 2260.2661 101.0 299.0 0.3378 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 27.0 33.0 73.0 0.4521 0.3699 41.0 45.0 78.0 0.5769 0.5256 14.0 22.0 83.0 0.2651 0.1687 0.0 0.0 1.0 0.0 0.0
0.0 19.0 19 7.6389 0.0058 3295.1529 2284.0259 102.0 299.0 0.3411 84.0 0.2809 0.0 1.0 64.0 0.0156 0.0 28.0 33.0 73.0 0.4521 0.3836 41.0 45.0 78.0 0.5769 0.5256 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 20.0 20 7.6509 0.0058 3300.3452 2287.6249 101.0 299.0 0.3378 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 41.0 45.0 78.0 0.5769 0.5256 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 21.0 21 7.7131 0.0058 3327.1709 2306.2191 102.0 299.0 0.3411 84.0 0.2809 0.0 1.0 64.0 0.0156 0.0 28.0 34.0 73.0 0.4658 0.3836 41.0 45.0 78.0 0.5769 0.5256 15.0 22.0 83.0 0.2651 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 22.0 22 7.7309 0.0058 3334.8353 2311.5317 103.0 299.0 0.3445 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 42.0 46.0 78.0 0.5897 0.5385 15.0 24.0 83.0 0.2892 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 23.0 23 7.7352 0.0058 3336.6981 2312.8229 103.0 299.0 0.3445 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 42.0 47.0 78.0 0.6026 0.5385 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 24.0 24 7.7672 0.0058 3350.5161 2322.4008 102.0 299.0 0.3411 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 41.0 46.0 78.0 0.5897 0.5256 15.0 24.0 83.0 0.2892 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 25.0 25 7.7816 0.0058 3356.7368 2326.7126 103.0 299.0 0.3445 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 41.0 46.0 78.0 0.5897 0.5256 15.0 24.0 83.0 0.2892 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 26.0 26 7.8011 0.0058 3365.1388 2332.5364 101.0 299.0 0.3378 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 41.0 45.0 78.0 0.5769 0.5256 14.0 23.0 83.0 0.2771 0.1687 0.0 0.0 1.0 0.0 0.0
0.0 27.0 27 7.8358 0.0058 3380.0976 2342.9051 101.0 299.0 0.3378 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 24.0 30.0 73.0 0.4110 0.3288 42.0 46.0 78.0 0.5897 0.5385 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 28.0 28 7.8089 0.0058 3368.4752 2334.8491 99.0 299.0 0.3311 80.0 0.2676 0.0 1.0 64.0 0.0156 0.0 24.0 30.0 73.0 0.4110 0.3288 40.0 44.0 78.0 0.5641 0.5128 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 29.0 29 7.8165 0.0058 3371.7741 2337.1357 101.0 299.0 0.3378 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 25.0 30.0 73.0 0.4110 0.3425 41.0 46.0 78.0 0.5897 0.5256 15.0 24.0 83.0 0.2892 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 30.0 30 7.8396 0.0058 3381.7473 2344.0486 103.0 299.0 0.3445 85.0 0.2843 0.0 1.0 64.0 0.0156 0.0 28.0 33.0 73.0 0.4521 0.3836 42.0 46.0 78.0 0.5897 0.5385 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 31.0 31 7.7978 0.0058 3363.7015 2331.5402 103.0 299.0 0.3445 85.0 0.2843 0.0 1.0 64.0 0.0156 0.0 27.0 32.0 73.0 0.4384 0.3699 42.0 46.0 78.0 0.5897 0.5385 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 32.0 32 7.8221 0.0058 3374.1689 2338.7957 100.0 299.0 0.3344 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 25.0 30.0 73.0 0.4110 0.3425 42.0 47.0 78.0 0.6026 0.5385 14.0 22.0 83.0 0.2651 0.1687 0.0 0.0 1.0 0.0 0.0
0.0 33.0 33 7.8283 0.0058 3376.8651 2340.6645 100.0 299.0 0.3344 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 25.0 30.0 73.0 0.4110 0.3425 41.0 46.0 78.0 0.5897 0.5256 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 34.0 34 7.8301 0.0058 3377.6460 2341.2058 102.0 299.0 0.3411 84.0 0.2809 0.0 1.0 64.0 0.0156 0.0 25.0 30.0 73.0 0.4110 0.3425 42.0 46.0 78.0 0.5897 0.5385 17.0 25.0 83.0 0.3012 0.2048 0.0 0.0 1.0 0.0 0.0
0.0 35.0 35 7.8523 0.0058 3387.2340 2347.8517 103.0 299.0 0.3445 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 42.0 47.0 78.0 0.6026 0.5385 15.0 24.0 83.0 0.2892 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 36.0 36 7.8513 0.0058 3386.7919 2347.5453 102.0 299.0 0.3411 85.0 0.2843 0.0 1.0 64.0 0.0156 0.0 26.0 30.0 73.0 0.4110 0.3562 42.0 46.0 78.0 0.5897 0.5385 17.0 25.0 83.0 0.3012 0.2048 0.0 0.0 1.0 0.0 0.0
0.0 37.0 37 7.8565 0.0058 3389.0261 2349.0939 103.0 299.0 0.3445 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 41.0 46.0 78.0 0.5897 0.5256 15.0 24.0 83.0 0.2892 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 38.0 38 7.8351 0.0058 3379.7752 2342.6816 104.0 299.0 0.3478 85.0 0.2843 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 42.0 47.0 78.0 0.6026 0.5385 17.0 24.0 83.0 0.2892 0.2048 0.0 0.0 1.0 0.0 0.0
0.0 39.0 39 7.8009 0.0058 3365.0442 2332.4709 106.0 299.0 0.3545 88.0 0.2943 0.0 1.0 64.0 0.0156 0.0 28.0 33.0 73.0 0.4521 0.3836 42.0 47.0 78.0 0.6026 0.5385 18.0 25.0 83.0 0.3012 0.2169 0.0 0.0 1.0 0.0 0.0
0.0 40.0 40 7.8364 0.0058 3380.3548 2343.0834 103.0 299.0 0.3445 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 27.0 33.0 73.0 0.4521 0.3699 41.0 46.0 78.0 0.5897 0.5256 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 41.0 41 7.8601 0.0058 3390.5641 2350.1599 103.0 299.0 0.3445 85.0 0.2843 0.0 1.0 64.0 0.0156 0.0 25.0 30.0 73.0 0.4110 0.3425 42.0 47.0 78.0 0.6026 0.5385 18.0 25.0 83.0 0.3012 0.2169 0.0 0.0 1.0 0.0 0.0
0.0 42.0 42 7.8950 0.0058 3405.6151 2360.5925 103.0 299.0 0.3445 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 42.0 47.0 78.0 0.6026 0.5385 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 43.0 43 7.8221 0.0058 3374.2062 2338.8215 103.0 299.0 0.3445 84.0 0.2809 0.0 1.0 64.0 0.0156 0.0 26.0 31.0 73.0 0.4247 0.3562 42.0 47.0 78.0 0.6026 0.5385 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 44.0 44 7.8410 0.0058 3382.3271 2344.4505 103.0 299.0 0.3445 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 41.0 47.0 78.0 0.6026 0.5256 14.0 23.0 83.0 0.2771 0.1687 0.0 0.0 1.0 0.0 0.0
0.0 45.0 45 7.8648 0.0058 3392.6239 2351.5877 100.0 299.0 0.3344 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 25.0 29.0 73.0 0.3973 0.3425 41.0 46.0 78.0 0.5897 0.5256 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 46.0 46 7.8424 0.0058 3382.9270 2344.8663 102.0 299.0 0.3411 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 26.0 31.0 73.0 0.4247 0.3562 41.0 46.0 78.0 0.5897 0.5256 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 47.0 47 7.8520 0.0058 3387.0809 2347.7456 101.0 299.0 0.3378 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 42.0 47.0 78.0 0.6026 0.5385 15.0 22.0 83.0 0.2651 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 48.0 48 7.8797 0.0058 3399.0337 2356.0306 103.0 299.0 0.3445 85.0 0.2843 0.0 1.0 64.0 0.0156 0.0 26.0 31.0 73.0 0.4247 0.3562 41.0 46.0 78.0 0.5897 0.5256 18.0 25.0 83.0 0.3012 0.2169 0.0 0.0 1.0 0.0 0.0
0.0 49.0 49 7.8223 0.0058 3374.2798 2338.8726 103.0 299.0 0.3445 85.0 0.2843 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 42.0 46.0 78.0 0.5897 0.5385 17.0 24.0 83.0 0.2892 0.2048 0.0 0.0 1.0 0.0 0.0
0.0 50.0 50 7.8456 0.0058 3384.3088 2345.8241 102.0 299.0 0.3411 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 25.0 30.0 73.0 0.4110 0.3425 41.0 46.0 78.0 0.5897 0.5256 17.0 25.0 83.0 0.3012 0.2048 0.0 0.0 1.0 0.0 0.0
0.0 51.0 51 7.8888 0.0058 3402.9783 2358.7648 101.0 299.0 0.3378 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 24.0 30.0 73.0 0.4110 0.3288 42.0 46.0 78.0 0.5897 0.5385 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 52.0 52 7.8554 0.0058 3388.5570 2348.7687 101.0 299.0 0.3378 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 24.0 30.0 73.0 0.4110 0.3288 42.0 46.0 78.0 0.5897 0.5385 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 53.0 53 7.8820 0.0058 3400.0236 2356.7168 99.0 299.0 0.3311 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 24.0 29.0 73.0 0.3973 0.3288 41.0 45.0 78.0 0.5769 0.5256 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 54.0 54 7.7962 0.0058 3363.0054 2331.0577 100.0 299.0 0.3344 80.0 0.2676 0.0 1.0 64.0 0.0156 0.0 23.0 29.0 73.0 0.3973 0.3151 41.0 46.0 78.0 0.5897 0.5256 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 55.0 55 7.8401 0.0058 3381.9685 2344.2019 104.0 299.0 0.3478 86.0 0.2876 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 42.0 46.0 78.0 0.5897 0.5385 18.0 25.0 83.0 0.3012 0.2169 0.0 0.0 1.0 0.0 0.0
0.0 56.0 56 7.8500 0.0058 3386.2261 2347.1531 103.0 299.0 0.3445 85.0 0.2843 0.0 1.0 64.0 0.0156 0.0 28.0 33.0 73.0 0.4521 0.3836 41.0 46.0 78.0 0.5897 0.5256 16.0 23.0 83.0 0.2771 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 57.0 57 7.8704 0.0058 3395.0304 2353.2557 103.0 299.0 0.3445 84.0 0.2809 0.0 1.0 64.0 0.0156 0.0 27.0 32.0 73.0 0.4384 0.3699 41.0 46.0 78.0 0.5897 0.5256 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 58.0 58 7.8215 0.0058 3373.9419 2338.6383 104.0 299.0 0.3478 84.0 0.2809 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 42.0 47.0 78.0 0.6026 0.5385 17.0 25.0 83.0 0.3012 0.2048 0.0 0.0 1.0 0.0 0.0
0.0 59.0 59 7.8851 0.0058 3401.3689 2357.6492 104.0 299.0 0.3478 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 26.0 32.0 73.0 0.4384 0.3562 41.0 47.0 78.0 0.6026 0.5256 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 60.0 60 7.8485 0.0058 3385.5608 2346.6920 102.0 299.0 0.3411 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 25.0 30.0 73.0 0.4110 0.3425 42.0 47.0 78.0 0.6026 0.5385 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 61.0 61 7.8927 0.0058 3404.6407 2359.9171 100.0 299.0 0.3344 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 25.0 30.0 73.0 0.4110 0.3425 41.0 46.0 78.0 0.5897 0.5256 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 62.0 62 7.8631 0.0058 3391.8588 2351.0574 101.0 299.0 0.3378 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 42.0 46.0 78.0 0.5897 0.5385 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 63.0 63 7.8690 0.0058 3394.4269 2352.8375 102.0 299.0 0.3411 82.0 0.2742 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 42.0 47.0 78.0 0.6026 0.5385 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 64.0 64 7.8658 0.0058 3393.0212 2351.8631 101.0 299.0 0.3378 83.0 0.2776 0.0 1.0 64.0 0.0156 0.0 26.0 31.0 73.0 0.4247 0.3562 41.0 45.0 78.0 0.5769 0.5256 16.0 24.0 83.0 0.2892 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 65.0 65 7.8915 0.0058 3404.1064 2359.5468 104.0 299.0 0.3478 86.0 0.2876 0.0 1.0 64.0 0.0156 0.0 28.0 33.0 73.0 0.4521 0.3836 42.0 47.0 78.0 0.6026 0.5385 16.0 23.0 83.0 0.2771 0.1928 0.0 0.0 1.0 0.0 0.0
0.0 66.0 66 7.9088 0.0058 3411.5654 2364.7169 104.0 299.0 0.3478 84.0 0.2809 0.0 1.0 64.0 0.0156 0.0 27.0 32.0 73.0 0.4384 0.3699 40.0 46.0 78.0 0.5897 0.5128 17.0 25.0 83.0 0.3012 0.2048 0.0 0.0 1.0 0.0 0.0
0.0 67.0 67 7.8904 0.0058 3403.6449 2359.2269 101.0 299.0 0.3378 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 41.0 45.0 78.0 0.5769 0.5256 15.0 24.0 83.0 0.2892 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 68.0 68 7.8711 0.0058 3395.3138 2353.4522 102.0 299.0 0.3411 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 41.0 46.0 78.0 0.5897 0.5256 15.0 24.0 83.0 0.2892 0.1807 0.0 0.0 1.0 0.0 0.0
0.0 69.0 69 7.8756 0.0058 3397.2473 2354.7924 100.0 299.0 0.3344 81.0 0.2709 0.0 1.0 64.0 0.0156 0.0 25.0 31.0 73.0 0.4247 0.3425 41.0 45.0 78.0 0.5769 0.5256 15.0 23.0 83.0 0.2771 0.1807 0.0 0.0 1.0 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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