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---
tags:
- summarization
- generated_from_trainer
model-index:
- name: finetune-led2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetune-led2
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9753
- Rouge1 Precision: 0.2523
- Rouge1 Recall: 0.3403
- Rouge1 Fmeasure: 0.2864
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 Fmeasure | Rouge1 Precision | Rouge1 Recall |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:----------------:|:-------------:|
| 2.0588 | 0.06 | 10 | 2.6812 | 0.2738 | 0.2434 | 0.3302 |
| 1.89 | 0.13 | 20 | 2.5273 | 0.2786 | 0.2527 | 0.3216 |
| 1.7108 | 0.19 | 30 | 2.4943 | 0.281 | 0.2471 | 0.337 |
| 1.6632 | 0.26 | 40 | 2.4320 | 0.2805 | 0.2456 | 0.3387 |
| 1.6764 | 0.32 | 50 | 2.3851 | 0.2806 | 0.2473 | 0.3352 |
| 1.6218 | 0.38 | 60 | 2.3718 | 0.2741 | 0.2395 | 0.3306 |
| 1.6105 | 0.11 | 70 | 2.3655 | 0.2851 | 0.2486 | 0.3446 |
| 1.6344 | 0.13 | 80 | 2.3529 | 0.2798 | 0.2485 | 0.3301 |
| 1.6359 | 0.14 | 90 | 2.3933 | 0.2845 | 0.2505 | 0.3394 |
| 1.5291 | 0.16 | 100 | 2.4088 | 0.2802 | 0.2453 | 0.3375 |
| 1.483 | 0.18 | 110 | 2.3258 | 0.2891 | 0.2575 | 0.3397 |
| 1.5317 | 0.19 | 120 | 2.2498 | 0.2785 | 0.2508 | 0.3223 |
| 1.5924 | 0.21 | 130 | 2.2690 | 0.2797 | 0.2471 | 0.3326 |
| 1.5086 | 0.22 | 140 | 2.3032 | 0.2768 | 0.2439 | 0.33 |
| 1.4654 | 0.24 | 150 | 2.2767 | 0.2792 | 0.2511 | 0.324 |
| 1.4575 | 0.26 | 160 | 2.2510 | 0.2825 | 0.2493 | 0.3356 |
| 1.5274 | 0.27 | 170 | 2.2635 | 0.2787 | 0.2446 | 0.3338 |
| 1.4993 | 0.29 | 180 | 2.2363 | 0.2845 | 0.2496 | 0.3406 |
| 1.5557 | 0.3 | 190 | 2.2319 | 0.282 | 0.2479 | 0.3364 |
| 1.476 | 0.32 | 200 | 2.2196 | 0.2735 | 0.2437 | 0.3216 |
| 1.4695 | 0.34 | 210 | 2.2604 | 0.2828 | 0.2477 | 0.3394 |
| 1.4819 | 0.35 | 220 | 2.2487 | 0.2806 | 0.2481 | 0.3329 |
| 1.4132 | 0.37 | 230 | 2.2176 | 0.2903 | 0.2543 | 0.348 |
| 1.4574 | 0.38 | 240 | 2.1912 | 0.2847 | 0.2513 | 0.3378 |
| 1.5263 | 0.4 | 250 | 2.1772 | 0.2761 | 0.2463 | 0.3234 |
| 1.4955 | 0.42 | 260 | 2.2065 | 0.2859 | 0.2483 | 0.3467 |
| 1.4698 | 0.43 | 270 | 2.1837 | 0.2831 | 0.2495 | 0.3368 |
| 1.5245 | 0.45 | 280 | 2.1769 | 0.2846 | 0.2513 | 0.3377 |
| 1.4691 | 0.46 | 290 | 2.1495 | 0.2832 | 0.252 | 0.3326 |
| 1.4203 | 0.48 | 300 | 2.1742 | 0.2791 | 0.2483 | 0.328 |
| 1.4827 | 0.5 | 310 | 2.1789 | 0.2793 | 0.2445 | 0.335 |
| 1.4478 | 0.51 | 320 | 2.1456 | 0.279 | 0.2483 | 0.328 |
| 1.4188 | 0.53 | 330 | 2.1637 | 0.2795 | 0.2499 | 0.3268 |
| 1.4096 | 0.54 | 340 | 2.1568 | 0.2863 | 0.2522 | 0.3407 |
| 1.4355 | 0.56 | 350 | 2.1613 | 0.2818 | 0.2467 | 0.3384 |
| 1.4587 | 0.58 | 360 | 2.1394 | 0.278 | 0.2441 | 0.3319 |
| 1.4674 | 0.59 | 370 | 2.1284 | 0.2818 | 0.2503 | 0.3317 |
| 1.3842 | 0.61 | 380 | 2.1286 | 0.2828 | 0.2521 | 0.3311 |
| 1.456 | 0.62 | 390 | 2.1013 | 0.2806 | 0.2513 | 0.3268 |
| 1.3512 | 0.64 | 400 | 2.1385 | 0.2817 | 0.2463 | 0.3384 |
| 1.3697 | 0.66 | 410 | 2.1282 | 0.2779 | 0.2451 | 0.3303 |
| 1.4404 | 0.67 | 420 | 2.1087 | 0.2837 | 0.2498 | 0.3376 |
| 1.4956 | 0.69 | 430 | 2.1034 | 0.2773 | 0.2446 | 0.3293 |
| 1.5532 | 0.7 | 440 | 2.1103 | 0.2834 | 0.2471 | 0.342 |
| 1.3254 | 0.72 | 450 | 2.1337 | 0.2811 | 0.2466 | 0.3363 |
| 1.4318 | 0.74 | 460 | 2.0690 | 0.287 | 0.2548 | 0.3382 |
| 1.3766 | 0.75 | 470 | 2.1392 | 0.2837 | 0.2438 | 0.3487 |
| 1.318 | 0.77 | 480 | 2.1353 | 0.2864 | 0.2492 | 0.3465 |
| 1.343 | 0.78 | 490 | 2.1262 | 0.282 | 0.2478 | 0.3375 |
| 1.3887 | 0.8 | 500 | 2.1246 | 0.2904 | 0.2552 | 0.3471 |
| 1.4047 | 0.82 | 510 | 2.0871 | 0.2835 | 0.2552 | 0.3285 |
| 1.459 | 0.83 | 520 | 2.1219 | 0.2824 | 0.247 | 0.3391 |
| 1.5071 | 0.85 | 530 | 2.0846 | 0.2799 | 0.2472 | 0.3321 |
| 1.3899 | 0.86 | 540 | 2.1019 | 0.2857 | 0.2505 | 0.3416 |
| 1.4277 | 0.88 | 550 | 2.0739 | 0.2831 | 0.2503 | 0.335 |
| 1.3651 | 0.9 | 560 | 2.0838 | 0.2788 | 0.2458 | 0.3312 |
| 1.4135 | 0.91 | 570 | 2.0783 | 0.2878 | 0.2547 | 0.3403 |
| 1.4165 | 0.93 | 580 | 2.0414 | 0.2848 | 0.2554 | 0.3311 |
| 1.3862 | 0.94 | 590 | 2.0631 | 0.2824 | 0.2497 | 0.3343 |
| 1.3839 | 0.96 | 600 | 2.0496 | 0.2778 | 0.2477 | 0.3252 |
| 1.3881 | 0.98 | 610 | 2.0682 | 0.2836 | 0.2492 | 0.3387 |
| 1.4462 | 0.99 | 620 | 2.0703 | 0.2824 | 0.2492 | 0.3355 |
| 1.3299 | 1.01 | 630 | 2.0345 | 0.2932 | 0.2607 | 0.3444 |
| 1.2978 | 1.02 | 640 | 2.0593 | 0.2868 | 0.2524 | 0.3416 |
| 1.2671 | 1.04 | 650 | 2.0719 | 0.285 | 0.2519 | 0.3382 |
| 1.2823 | 1.06 | 660 | 2.0529 | 0.2838 | 0.2542 | 0.3307 |
| 1.2797 | 1.07 | 670 | 2.0745 | 0.2867 | 0.2518 | 0.3424 |
| 1.3185 | 1.09 | 680 | 2.0725 | 0.2795 | 0.2465 | 0.3324 |
| 1.3278 | 1.1 | 690 | 2.0492 | 0.2881 | 0.2541 | 0.3422 |
| 1.3344 | 1.12 | 700 | 2.0541 | 0.2869 | 0.251 | 0.3442 |
| 1.2929 | 1.14 | 710 | 2.0588 | 0.2834 | 0.2487 | 0.339 |
| 1.2152 | 1.15 | 720 | 2.0515 | 0.2884 | 0.254 | 0.3427 |
| 1.2662 | 1.17 | 730 | 2.0552 | 0.2777 | 0.2452 | 0.3295 |
| 1.2999 | 1.18 | 740 | 2.0337 | 0.2823 | 0.2512 | 0.3314 |
| 1.327 | 1.2 | 750 | 2.0363 | 0.2843 | 0.2486 | 0.3416 |
| 1.2588 | 1.22 | 760 | 2.0550 | 0.2889 | 0.2549 | 0.3437 |
| 1.2676 | 1.23 | 770 | 2.0146 | 0.2819 | 0.2483 | 0.3351 |
| 1.3498 | 1.25 | 780 | 2.0291 | 0.2812 | 0.2475 | 0.3348 |
| 1.3004 | 1.26 | 790 | 2.0501 | 0.2836 | 0.2484 | 0.3398 |
| 1.2663 | 1.28 | 800 | 2.0205 | 0.2838 | 0.2505 | 0.3364 |
| 1.2419 | 1.3 | 810 | 2.0274 | 0.2837 | 0.2511 | 0.3353 |
| 1.3022 | 1.31 | 820 | 2.0277 | 0.2838 | 0.2496 | 0.3376 |
| 1.3404 | 1.33 | 830 | 2.0417 | 0.2835 | 0.2491 | 0.3384 |
| 1.2684 | 1.34 | 840 | 2.0474 | 0.2841 | 0.2485 | 0.3412 |
| 1.3272 | 1.36 | 850 | 2.0520 | 0.2889 | 0.254 | 0.3444 |
| 1.2133 | 1.38 | 860 | 2.0172 | 0.2848 | 0.2521 | 0.3367 |
| 1.2698 | 1.39 | 870 | 2.0031 | 0.2864 | 0.2536 | 0.3382 |
| 1.1931 | 1.41 | 880 | 2.0211 | 0.2832 | 0.2507 | 0.3349 |
| 1.2514 | 1.42 | 890 | 2.0176 | 0.2904 | 0.2551 | 0.3464 |
| 1.3456 | 1.44 | 900 | 1.9953 | 0.2769 | 0.243 | 0.3308 |
| 1.2857 | 1.46 | 910 | 1.9979 | 0.2891 | 0.2542 | 0.3447 |
| 1.2462 | 1.47 | 920 | 2.0191 | 0.2842 | 0.2485 | 0.3414 |
| 1.2398 | 1.49 | 930 | 1.9891 | 0.2854 | 0.253 | 0.3368 |
| 1.2982 | 1.5 | 940 | 1.9947 | 0.2894 | 0.2566 | 0.3416 |
| 1.2334 | 1.52 | 950 | 1.9975 | 0.287 | 0.2512 | 0.3444 |
| 1.2572 | 1.54 | 960 | 1.9977 | 0.288 | 0.2539 | 0.3424 |
| 1.1719 | 1.55 | 970 | 2.0149 | 0.2857 | 0.2514 | 0.3404 |
| 1.1536 | 1.57 | 980 | 1.9899 | 0.2905 | 0.2558 | 0.3456 |
| 1.2731 | 1.58 | 990 | 1.9915 | 0.2864 | 0.2528 | 0.3401 |
| 1.2694 | 1.6 | 1000 | 2.0039 | 0.2872 | 0.252 | 0.3434 |
| 1.2481 | 1.62 | 1010 | 2.0071 | 0.2806 | 0.2467 | 0.335 |
| 1.1825 | 1.63 | 1020 | 1.9943 | 0.2862 | 0.2514 | 0.3417 |
| 1.2626 | 1.65 | 1030 | 1.9953 | 0.2837 | 0.2489 | 0.3396 |
| 1.2497 | 1.66 | 1040 | 2.0078 | 0.287 | 0.2511 | 0.3444 |
| 1.2401 | 1.68 | 1050 | 1.9765 | 0.2853 | 0.2501 | 0.3422 |
| 1.2074 | 1.7 | 1060 | 1.9970 | 0.2863 | 0.252 | 0.3412 |
| 1.1557 | 1.71 | 1070 | 1.9860 | 0.2841 | 0.2492 | 0.34 |
| 1.1298 | 1.73 | 1080 | 1.9895 | 0.2862 | 0.2525 | 0.3397 |
| 1.1531 | 1.74 | 1090 | 1.9813 | 0.2892 | 0.2546 | 0.3442 |
| 1.2627 | 1.76 | 1100 | 1.9906 | 0.2863 | 0.2522 | 0.3407 |
| 1.2191 | 1.78 | 1110 | 1.9853 | 0.2879 | 0.253 | 0.3435 |
| 1.2415 | 1.79 | 1120 | 1.9927 | 0.288 | 0.2541 | 0.342 |
| 1.2879 | 1.81 | 1130 | 1.9839 | 0.2831 | 0.2491 | 0.3378 |
| 1.2328 | 1.82 | 1140 | 1.9698 | 0.2852 | 0.2526 | 0.337 |
| 1.2562 | 1.84 | 1150 | 1.9953 | 0.2866 | 0.2504 | 0.3444 |
| 1.3071 | 1.86 | 1160 | 1.9698 | 0.2847 | 0.2507 | 0.3389 |
| 1.2276 | 1.87 | 1170 | 1.9787 | 0.2863 | 0.2517 | 0.3415 |
| 1.1608 | 1.89 | 1180 | 1.9944 | 0.289 | 0.2528 | 0.3469 |
| 1.3046 | 1.9 | 1190 | 1.9750 | 0.2863 | 0.2516 | 0.3414 |
| 1.2468 | 1.92 | 1200 | 1.9742 | 0.2841 | 0.2503 | 0.338 |
| 1.2839 | 1.94 | 1210 | 1.9812 | 0.2841 | 0.2497 | 0.3392 |
| 1.2117 | 1.95 | 1220 | 1.9755 | 0.2847 | 0.2507 | 0.3384 |
| 1.2055 | 1.97 | 1230 | 1.9759 | 0.2855 | 0.2516 | 0.3393 |
| 1.2356 | 1.98 | 1240 | 1.9747 | 0.286 | 0.2522 | 0.3399 |
| 1.1865 | 2.0 | 1250 | 1.9753 | 0.2863 | 0.2523 | 0.3404 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.15.1
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