Hugging Face's logo

donoway
/
ARC-Easy_Llama-3.2-1B-oqrx1b71

Text Generation
Transformers
Safetensors
llama
Generated from Trainer
text-generation-inference
Model card Files
xet
Community

ARC-Easy_Llama-3.2-1B-oqrx1b71

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: 3.7385
  • Model Preparation Time: 0.0069
  • Mdl: 3074.3332
  • Accumulated Loss: 2130.9654
  • Correct Preds: 371.0
  • Total Preds: 570.0
  • Accuracy: 0.6509
  • Correct Gen Preds: 326.0
  • Gen Accuracy: 0.5719
  • Correct Gen Preds 32: 79.0
  • Correct Preds 32: 103.0
  • Total Labels 32: 158.0
  • Accuracy 32: 0.6519
  • Gen Accuracy 32: 0.5
  • Correct Gen Preds 33: 110.0
  • Correct Preds 33: 113.0
  • Total Labels 33: 152.0
  • Accuracy 33: 0.7434
  • Gen Accuracy 33: 0.7237
  • Correct Gen Preds 34: 91.0
  • Correct Preds 34: 99.0
  • Total Labels 34: 142.0
  • Accuracy 34: 0.6972
  • Gen Accuracy 34: 0.6408
  • Correct Gen Preds 35: 46.0
  • Correct Preds 35: 56.0
  • Total Labels 35: 118.0
  • Accuracy 35: 0.4746
  • Gen Accuracy 35: 0.3898
  • 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
1.4592 1.0 1 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
1.4587 2.0 2 2.8572 0.0069 2349.6051 1628.6221 188.0 570.0 0.3298 188.0 0.3298 0.0 0.0 158.0 0.0 0.0 46.0 46.0 152.0 0.3026 0.3026 141.0 141.0 142.0 0.9930 0.9930 1.0 1.0 118.0 0.0085 0.0085 0.0 0.0 0.0 0.0 0.0
1.7615 3.0 3 1.5150 0.0069 1245.8152 863.5333 173.0 570.0 0.3035 173.0 0.3035 0.0 0.0 158.0 0.0 0.0 151.0 151.0 152.0 0.9934 0.9934 8.0 8.0 142.0 0.0563 0.0563 14.0 14.0 118.0 0.1186 0.1186 0.0 0.0 0.0 0.0 0.0
0.683 4.0 4 1.3806 0.0069 1135.3136 786.9394 307.0 570.0 0.5386 254.0 0.4456 39.0 59.0 158.0 0.3734 0.2468 107.0 126.0 152.0 0.8289 0.7039 76.0 84.0 142.0 0.5915 0.5352 32.0 38.0 118.0 0.3220 0.2712 0.0 0.0 0.0 0.0 0.0
0.0591 5.0 5 1.8312 0.0069 1505.8471 1043.7737 356.0 570.0 0.6246 262.0 0.4596 53.0 98.0 158.0 0.6203 0.3354 98.0 115.0 152.0 0.7566 0.6447 69.0 92.0 142.0 0.6479 0.4859 42.0 51.0 118.0 0.4322 0.3559 0.0 0.0 0.0 0.0 0.0
0.0003 6.0 6 2.3233 0.0069 1910.5098 1324.2645 353.0 570.0 0.6193 288.0 0.5053 64.0 97.0 158.0 0.6139 0.4051 103.0 113.0 152.0 0.7434 0.6776 75.0 90.0 142.0 0.6338 0.5282 46.0 53.0 118.0 0.4492 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 7.0 7 2.6634 0.0069 2190.2029 1518.1330 366.0 570.0 0.6421 306.0 0.5368 66.0 101.0 158.0 0.6392 0.4177 108.0 115.0 152.0 0.7566 0.7105 81.0 95.0 142.0 0.6690 0.5704 51.0 55.0 118.0 0.4661 0.4322 0.0 0.0 0.0 0.0 0.0
0.0 8.0 8 2.9283 0.0069 2408.0786 1669.1529 365.0 570.0 0.6404 313.0 0.5491 67.0 101.0 158.0 0.6392 0.4241 109.0 113.0 152.0 0.7434 0.7171 87.0 96.0 142.0 0.6761 0.6127 50.0 55.0 118.0 0.4661 0.4237 0.0 0.0 0.0 0.0 0.0
0.0 9.0 9 3.1394 0.0069 2581.6660 1789.4745 370.0 570.0 0.6491 318.0 0.5579 70.0 104.0 158.0 0.6582 0.4430 110.0 115.0 152.0 0.7566 0.7237 88.0 97.0 142.0 0.6831 0.6197 50.0 54.0 118.0 0.4576 0.4237 0.0 0.0 0.0 0.0 0.0
0.0 10.0 10 3.2952 0.0069 2709.7573 1878.2607 368.0 570.0 0.6456 314.0 0.5509 73.0 101.0 158.0 0.6392 0.4620 109.0 114.0 152.0 0.75 0.7171 86.0 98.0 142.0 0.6901 0.6056 46.0 55.0 118.0 0.4661 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 11.0 11 3.4102 0.0069 2804.3076 1943.7979 366.0 570.0 0.6421 318.0 0.5579 74.0 100.0 158.0 0.6329 0.4684 109.0 114.0 152.0 0.75 0.7171 89.0 98.0 142.0 0.6901 0.6268 46.0 54.0 118.0 0.4576 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 12.0 12 3.4933 0.0069 2872.6570 1991.1741 366.0 570.0 0.6421 320.0 0.5614 74.0 100.0 158.0 0.6329 0.4684 110.0 114.0 152.0 0.75 0.7237 90.0 98.0 142.0 0.6901 0.6338 46.0 54.0 118.0 0.4576 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 13.0 13 3.5624 0.0069 2929.5074 2030.5798 364.0 570.0 0.6386 318.0 0.5579 75.0 100.0 158.0 0.6329 0.4747 109.0 113.0 152.0 0.7434 0.7171 88.0 97.0 142.0 0.6831 0.6197 46.0 54.0 118.0 0.4576 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 14.0 14 3.6095 0.0069 2968.2088 2057.4056 365.0 570.0 0.6404 318.0 0.5579 71.0 100.0 158.0 0.6329 0.4494 111.0 114.0 152.0 0.75 0.7303 90.0 97.0 142.0 0.6831 0.6338 46.0 54.0 118.0 0.4576 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 15.0 15 3.6542 0.0069 3004.9703 2082.8867 368.0 570.0 0.6456 319.0 0.5596 73.0 102.0 158.0 0.6456 0.4620 110.0 113.0 152.0 0.7434 0.7237 90.0 98.0 142.0 0.6901 0.6338 46.0 55.0 118.0 0.4661 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 16.0 16 3.6640 0.0069 3013.0252 2088.4699 367.0 570.0 0.6439 321.0 0.5632 73.0 101.0 158.0 0.6392 0.4620 111.0 114.0 152.0 0.75 0.7303 91.0 98.0 142.0 0.6901 0.6408 46.0 54.0 118.0 0.4576 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 17.0 17 3.6991 0.0069 3041.8667 2108.4613 369.0 570.0 0.6474 321.0 0.5632 76.0 103.0 158.0 0.6519 0.4810 109.0 113.0 152.0 0.7434 0.7171 90.0 98.0 142.0 0.6901 0.6338 46.0 55.0 118.0 0.4661 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 18.0 18 3.7206 0.0069 3059.5550 2120.7219 370.0 570.0 0.6491 321.0 0.5632 77.0 104.0 158.0 0.6582 0.4873 109.0 113.0 152.0 0.7434 0.7171 89.0 97.0 142.0 0.6831 0.6268 46.0 56.0 118.0 0.4746 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 19.0 19 3.7281 0.0069 3065.7453 2125.0127 368.0 570.0 0.6456 320.0 0.5614 74.0 102.0 158.0 0.6456 0.4684 110.0 114.0 152.0 0.75 0.7237 90.0 98.0 142.0 0.6901 0.6338 46.0 54.0 118.0 0.4576 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 20.0 20 3.7380 0.0069 3073.8754 2130.6481 369.0 570.0 0.6474 321.0 0.5632 77.0 102.0 158.0 0.6456 0.4873 109.0 114.0 152.0 0.75 0.7171 90.0 97.0 142.0 0.6831 0.6338 45.0 56.0 118.0 0.4746 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 21.0 21 3.7385 0.0069 3074.3332 2130.9654 371.0 570.0 0.6509 326.0 0.5719 79.0 103.0 158.0 0.6519 0.5 110.0 113.0 152.0 0.7434 0.7237 91.0 99.0 142.0 0.6972 0.6408 46.0 56.0 118.0 0.4746 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 22.0 22 3.7640 0.0069 3095.2993 2145.4980 366.0 570.0 0.6421 319.0 0.5596 75.0 101.0 158.0 0.6392 0.4747 108.0 113.0 152.0 0.7434 0.7105 90.0 97.0 142.0 0.6831 0.6338 46.0 55.0 118.0 0.4661 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 23.0 23 3.7726 0.0069 3102.3483 2150.3840 367.0 570.0 0.6439 325.0 0.5702 81.0 102.0 158.0 0.6456 0.5127 108.0 112.0 152.0 0.7368 0.7105 90.0 98.0 142.0 0.6901 0.6338 46.0 55.0 118.0 0.4661 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 24.0 24 3.7770 0.0069 3105.9931 2152.9104 368.0 570.0 0.6456 321.0 0.5632 76.0 102.0 158.0 0.6456 0.4810 109.0 112.0 152.0 0.7368 0.7171 90.0 98.0 142.0 0.6901 0.6338 46.0 56.0 118.0 0.4746 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 25.0 25 3.7813 0.0069 3109.4856 2155.3312 367.0 570.0 0.6439 322.0 0.5649 78.0 103.0 158.0 0.6519 0.4937 109.0 112.0 152.0 0.7368 0.7171 90.0 98.0 142.0 0.6901 0.6338 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 26.0 26 3.7764 0.0069 3105.4752 2152.5513 367.0 570.0 0.6439 322.0 0.5649 79.0 103.0 158.0 0.6519 0.5 109.0 112.0 152.0 0.7368 0.7171 89.0 97.0 142.0 0.6831 0.6268 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 27.0 27 3.7828 0.0069 3110.7617 2156.2157 365.0 570.0 0.6404 321.0 0.5632 79.0 102.0 158.0 0.6456 0.5 108.0 112.0 152.0 0.7368 0.7105 89.0 97.0 142.0 0.6831 0.6268 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 28.0 28 3.7887 0.0069 3115.5792 2159.5549 367.0 570.0 0.6439 321.0 0.5632 78.0 102.0 158.0 0.6456 0.4937 108.0 111.0 152.0 0.7303 0.7105 90.0 99.0 142.0 0.6972 0.6338 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 29.0 29 3.7980 0.0069 3123.2559 2164.8760 366.0 570.0 0.6421 324.0 0.5684 79.0 102.0 158.0 0.6456 0.5 109.0 112.0 152.0 0.7368 0.7171 91.0 98.0 142.0 0.6901 0.6408 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 30.0 30 3.7857 0.0069 3113.0984 2157.8354 369.0 570.0 0.6474 325.0 0.5702 79.0 102.0 158.0 0.6456 0.5 110.0 114.0 152.0 0.75 0.7237 92.0 99.0 142.0 0.6972 0.6479 44.0 54.0 118.0 0.4576 0.3729 0.0 0.0 0.0 0.0 0.0
0.0 31.0 31 3.8105 0.0069 3133.4788 2171.9620 367.0 570.0 0.6439 323.0 0.5667 78.0 103.0 158.0 0.6519 0.4937 109.0 111.0 152.0 0.7303 0.7171 91.0 98.0 142.0 0.6901 0.6408 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 32.0 32 3.7983 0.0069 3123.4747 2165.0277 368.0 570.0 0.6456 323.0 0.5667 80.0 103.0 158.0 0.6519 0.5063 109.0 112.0 152.0 0.7368 0.7171 89.0 98.0 142.0 0.6901 0.6268 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 33.0 33 3.7838 0.0069 3111.5678 2156.7744 368.0 570.0 0.6456 320.0 0.5614 77.0 102.0 158.0 0.6456 0.4873 108.0 112.0 152.0 0.7368 0.7105 90.0 98.0 142.0 0.6901 0.6338 45.0 56.0 118.0 0.4746 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 34.0 34 3.8000 0.0069 3124.8632 2165.9901 366.0 570.0 0.6421 320.0 0.5614 79.0 103.0 158.0 0.6519 0.5 108.0 111.0 152.0 0.7303 0.7105 88.0 97.0 142.0 0.6831 0.6197 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 35.0 35 3.8131 0.0069 3135.6651 2173.4774 363.0 570.0 0.6368 320.0 0.5614 79.0 102.0 158.0 0.6456 0.5 107.0 110.0 152.0 0.7237 0.7039 89.0 97.0 142.0 0.6831 0.6268 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 36.0 36 3.7965 0.0069 3121.9935 2164.0010 367.0 570.0 0.6439 322.0 0.5649 79.0 102.0 158.0 0.6456 0.5 109.0 113.0 152.0 0.7434 0.7171 89.0 98.0 142.0 0.6901 0.6268 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 37.0 37 3.7996 0.0069 3124.5287 2165.7583 368.0 570.0 0.6456 322.0 0.5649 79.0 103.0 158.0 0.6519 0.5 109.0 113.0 152.0 0.7434 0.7171 89.0 97.0 142.0 0.6831 0.6268 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 38.0 38 3.7855 0.0069 3112.9473 2157.7307 369.0 570.0 0.6474 324.0 0.5684 79.0 103.0 158.0 0.6519 0.5 110.0 113.0 152.0 0.7434 0.7237 91.0 99.0 142.0 0.6972 0.6408 44.0 54.0 118.0 0.4576 0.3729 0.0 0.0 0.0 0.0 0.0
0.0 39.0 39 3.7976 0.0069 3122.9250 2164.6467 366.0 570.0 0.6421 322.0 0.5649 79.0 102.0 158.0 0.6456 0.5 108.0 111.0 152.0 0.7303 0.7105 89.0 97.0 142.0 0.6831 0.6268 46.0 56.0 118.0 0.4746 0.3898 0.0 0.0 0.0 0.0 0.0
0.0 40.0 40 3.7913 0.0069 3117.7141 2161.0348 366.0 570.0 0.6421 323.0 0.5667 79.0 102.0 158.0 0.6456 0.5 109.0 112.0 152.0 0.7368 0.7171 90.0 98.0 142.0 0.6901 0.6338 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 41.0 41 3.8044 0.0069 3128.4659 2168.4873 370.0 570.0 0.6491 321.0 0.5632 78.0 103.0 158.0 0.6519 0.4937 107.0 112.0 152.0 0.7368 0.7039 91.0 99.0 142.0 0.6972 0.6408 45.0 56.0 118.0 0.4746 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 42.0 42 3.8034 0.0069 3127.6742 2167.9386 367.0 570.0 0.6439 323.0 0.5667 79.0 103.0 158.0 0.6519 0.5 110.0 113.0 152.0 0.7434 0.7237 89.0 96.0 142.0 0.6761 0.6268 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 43.0 43 3.7958 0.0069 3121.3983 2163.5884 367.0 570.0 0.6439 323.0 0.5667 80.0 102.0 158.0 0.6456 0.5063 108.0 112.0 152.0 0.7368 0.7105 90.0 97.0 142.0 0.6831 0.6338 45.0 56.0 118.0 0.4746 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 44.0 44 3.8052 0.0069 3129.1145 2168.9369 366.0 570.0 0.6421 321.0 0.5632 77.0 101.0 158.0 0.6392 0.4873 108.0 112.0 152.0 0.7368 0.7105 91.0 98.0 142.0 0.6901 0.6408 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 45.0 45 3.7989 0.0069 3123.9498 2165.3570 367.0 570.0 0.6439 324.0 0.5684 79.0 102.0 158.0 0.6456 0.5 110.0 113.0 152.0 0.7434 0.7237 90.0 98.0 142.0 0.6901 0.6338 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 46.0 46 3.8045 0.0069 3128.6029 2168.5823 369.0 570.0 0.6474 322.0 0.5649 76.0 102.0 158.0 0.6456 0.4810 109.0 113.0 152.0 0.7434 0.7171 92.0 99.0 142.0 0.6972 0.6479 45.0 55.0 118.0 0.4661 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 47.0 47 3.8041 0.0069 3128.2620 2168.3460 367.0 570.0 0.6439 324.0 0.5684 81.0 103.0 158.0 0.6519 0.5127 108.0 112.0 152.0 0.7368 0.7105 90.0 98.0 142.0 0.6901 0.6338 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 48.0 48 3.7913 0.0069 3117.7010 2161.0257 367.0 570.0 0.6439 321.0 0.5632 77.0 102.0 158.0 0.6456 0.4873 108.0 112.0 152.0 0.7368 0.7105 91.0 99.0 142.0 0.6972 0.6408 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 49.0 49 3.8082 0.0069 3131.6407 2170.6880 365.0 570.0 0.6404 321.0 0.5632 78.0 101.0 158.0 0.6392 0.4937 108.0 112.0 152.0 0.7368 0.7105 90.0 98.0 142.0 0.6901 0.6338 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 50.0 50 3.8087 0.0069 3132.0417 2170.9659 367.0 570.0 0.6439 322.0 0.5649 78.0 103.0 158.0 0.6519 0.4937 109.0 112.0 152.0 0.7368 0.7171 90.0 98.0 142.0 0.6901 0.6338 45.0 54.0 118.0 0.4576 0.3814 0.0 0.0 0.0 0.0 0.0
0.0 51.0 51 3.7933 0.0069 3119.3595 2162.1753 368.0 570.0 0.6456 321.0 0.5632 77.0 102.0 158.0 0.6456 0.4873 109.0 112.0 152.0 0.7368 0.7171 90.0 98.0 142.0 0.6901 0.6338 45.0 56.0 118.0 0.4746 0.3814 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
Downloads last month
1
Safetensors
Model size
1B params
Tensor type
BF16
·
Inference Providers NEW
Text Generation
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for donoway/ARC-Easy_Llama-3.2-1B-oqrx1b71

Base model

meta-llama/Llama-3.2-1B
Finetuned
(884)
this model