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tinh2312
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SignBart-ASL-100

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bart
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How to use from the
Use from the
Transformers library
# Load model directly
from transformers import AutoTokenizer, SignBart

tokenizer = AutoTokenizer.from_pretrained("tinh2312/SignBart-ASL-100")
model = SignBart.from_pretrained("tinh2312/SignBart-ASL-100", device_map="auto")
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SignBart-ASL-100

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8835
  • Accuracy: 0.7960
  • Precision: 0.8112
  • Recall: 0.7960

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: 0.0002
  • train_batch_size: 256
  • eval_batch_size: 256
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.5
  • num_epochs: 1000

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall
4.6468 1.0 10 4.6285 0.0072 0.0009 0.0072
4.6453 2.0 20 4.6284 0.0072 0.0009 0.0072
4.6469 3.0 30 4.6283 0.0072 0.0009 0.0072
4.656 4.0 40 4.6282 0.0081 0.0009 0.0081
4.645 5.0 50 4.6280 0.0081 0.0009 0.0081
4.65 6.0 60 4.6278 0.0081 0.0009 0.0081
4.6405 7.0 70 4.6275 0.0081 0.0009 0.0081
4.6444 8.0 80 4.6273 0.0072 0.0008 0.0072
4.6538 9.0 90 4.6270 0.0063 0.0007 0.0063
4.6421 10.0 100 4.6266 0.0063 0.0007 0.0063
4.6368 11.0 110 4.6262 0.0063 0.0007 0.0063
4.6389 12.0 120 4.6258 0.0054 0.0006 0.0054
4.6449 13.0 130 4.6254 0.0054 0.0006 0.0054
4.6514 14.0 140 4.6249 0.0054 0.0006 0.0054
4.6402 15.0 150 4.6244 0.0063 0.0097 0.0063
4.6427 16.0 160 4.6239 0.0063 0.0097 0.0063
4.6349 17.0 170 4.6234 0.0072 0.0097 0.0072
4.654 18.0 180 4.6228 0.0072 0.0029 0.0072
4.652 19.0 190 4.6222 0.0081 0.0029 0.0081
4.6394 20.0 200 4.6216 0.0081 0.0022 0.0081
4.6421 21.0 210 4.6210 0.0072 0.0021 0.0072
4.6413 22.0 220 4.6204 0.0072 0.0019 0.0072
4.6354 23.0 230 4.6198 0.0072 0.0019 0.0072
4.656 24.0 240 4.6192 0.0063 0.0019 0.0063
4.6422 25.0 250 4.6185 0.0063 0.0017 0.0063
4.6298 26.0 260 4.6178 0.0081 0.0026 0.0081
4.6423 27.0 270 4.6171 0.0081 0.0026 0.0081
4.6361 28.0 280 4.6164 0.0081 0.0028 0.0081
4.6277 29.0 290 4.6157 0.0081 0.0025 0.0081
4.6405 30.0 300 4.6150 0.0081 0.0025 0.0081
4.6366 31.0 310 4.6144 0.0081 0.0025 0.0081
4.6324 32.0 320 4.6137 0.0081 0.0025 0.0081
4.6369 33.0 330 4.6130 0.0081 0.0025 0.0081
4.6181 34.0 340 4.6124 0.0081 0.0022 0.0081
4.6277 35.0 350 4.6117 0.0081 0.0022 0.0081
4.6295 36.0 360 4.6111 0.0081 0.0022 0.0081
4.6247 37.0 370 4.6104 0.0081 0.0021 0.0081
4.6242 38.0 380 4.6098 0.0081 0.0021 0.0081
4.631 39.0 390 4.6092 0.0081 0.0020 0.0081
4.6267 40.0 400 4.6085 0.0081 0.0022 0.0081
4.6209 41.0 410 4.6079 0.0081 0.0024 0.0081
4.6242 42.0 420 4.6073 0.0072 0.0016 0.0072
4.6228 43.0 430 4.6067 0.0081 0.0021 0.0081
4.6158 44.0 440 4.6061 0.0072 0.0020 0.0072
4.6222 45.0 450 4.6055 0.0072 0.0021 0.0072
4.6249 46.0 460 4.6049 0.0072 0.0021 0.0072
4.6297 47.0 470 4.6043 0.0063 0.0019 0.0063
4.6188 48.0 480 4.6036 0.0090 0.0030 0.0090
4.6178 49.0 490 4.6030 0.0090 0.0028 0.0090
4.6202 50.0 500 4.6023 0.0099 0.0028 0.0099
4.6172 51.0 510 4.6016 0.0090 0.0027 0.0090
4.6215 52.0 520 4.6009 0.0099 0.0027 0.0099
4.6159 53.0 530 4.6000 0.0099 0.0029 0.0099
4.6088 54.0 540 4.5992 0.0099 0.0027 0.0099
4.6151 55.0 550 4.5983 0.0099 0.0026 0.0099
4.6087 56.0 560 4.5973 0.0108 0.0027 0.0108
4.6098 57.0 570 4.5962 0.0108 0.0044 0.0108
4.6158 58.0 580 4.5949 0.0108 0.0037 0.0108
4.6125 59.0 590 4.5935 0.0108 0.0030 0.0108
4.607 60.0 600 4.5920 0.0126 0.0034 0.0126
4.6024 61.0 610 4.5903 0.0126 0.0031 0.0126
4.5983 62.0 620 4.5882 0.0144 0.0034 0.0144
4.6015 63.0 630 4.5860 0.0162 0.0053 0.0162
4.6095 64.0 640 4.5833 0.0162 0.0039 0.0162
4.5965 65.0 650 4.5802 0.0190 0.0045 0.0190
4.5841 66.0 660 4.5764 0.0181 0.0046 0.0181
4.5946 67.0 670 4.5717 0.0199 0.0048 0.0199
4.59 68.0 680 4.5667 0.0181 0.0046 0.0181
4.5793 69.0 690 4.5611 0.0262 0.0051 0.0262
4.5735 70.0 700 4.5543 0.0271 0.0050 0.0271
4.5774 71.0 710 4.5467 0.0289 0.0054 0.0289
4.5691 72.0 720 4.5384 0.0298 0.0053 0.0298
4.5494 73.0 730 4.5290 0.0244 0.0045 0.0244
4.5386 74.0 740 4.5178 0.0226 0.0043 0.0226
4.538 75.0 750 4.5048 0.0271 0.0071 0.0271
4.5289 76.0 760 4.4896 0.0289 0.0084 0.0289
4.5141 77.0 770 4.4715 0.0298 0.0092 0.0298
4.4996 78.0 780 4.4506 0.0334 0.0151 0.0334
4.501 79.0 790 4.4296 0.0298 0.0092 0.0298
4.4829 80.0 800 4.4109 0.0289 0.0104 0.0289
4.4827 81.0 810 4.3936 0.0280 0.0084 0.0280
4.4536 82.0 820 4.3770 0.0307 0.0193 0.0307
4.4675 83.0 830 4.3611 0.0325 0.0206 0.0325
4.4089 84.0 840 4.3453 0.0415 0.0346 0.0415
4.3945 85.0 850 4.3290 0.0397 0.0221 0.0397
4.4146 86.0 860 4.3140 0.0505 0.0232 0.0505
4.3668 87.0 870 4.2945 0.0469 0.0298 0.0469
4.3833 88.0 880 4.2785 0.0587 0.0353 0.0587
4.358 89.0 890 4.2603 0.0542 0.0265 0.0542
4.3412 90.0 900 4.2426 0.0578 0.0396 0.0578
4.3404 91.0 910 4.2251 0.0614 0.0416 0.0614
4.2978 92.0 920 4.2084 0.0695 0.0398 0.0695
4.3052 93.0 930 4.1897 0.0740 0.0492 0.0740
4.2866 94.0 940 4.1735 0.0749 0.0385 0.0749
4.2535 95.0 950 4.1572 0.0758 0.0343 0.0758
4.2331 96.0 960 4.1397 0.0767 0.0342 0.0767
4.1862 97.0 970 4.1234 0.0767 0.0371 0.0767
4.2058 98.0 980 4.1069 0.0758 0.0426 0.0758
4.1817 99.0 990 4.0918 0.0749 0.0334 0.0749
4.2257 100.0 1000 4.0779 0.0776 0.0455 0.0776
4.1975 101.0 1010 4.0648 0.0803 0.0413 0.0803
4.1815 102.0 1020 4.0522 0.0821 0.0318 0.0821
4.1534 103.0 1030 4.0367 0.0839 0.0311 0.0839
4.1966 104.0 1040 4.0244 0.0866 0.0414 0.0866
4.1424 105.0 1050 4.0146 0.0848 0.0449 0.0848
4.0961 106.0 1060 4.0016 0.0839 0.0512 0.0839
4.0821 107.0 1070 3.9865 0.0912 0.0585 0.0912
4.0785 108.0 1080 3.9752 0.0975 0.0437 0.0975
4.0733 109.0 1090 3.9623 0.1002 0.0458 0.1002
4.1087 110.0 1100 3.9467 0.1083 0.0718 0.1083
4.0278 111.0 1110 3.9361 0.1200 0.1107 0.1200
4.0094 112.0 1120 3.9212 0.1173 0.0821 0.1173
4.0206 113.0 1130 3.9102 0.1218 0.0862 0.1218
4.0174 114.0 1140 3.8972 0.1291 0.1162 0.1291
3.9941 115.0 1150 3.8840 0.1264 0.1012 0.1264
3.991 116.0 1160 3.8721 0.1354 0.1165 0.1354
4.0254 117.0 1170 3.8602 0.1363 0.1247 0.1363
4.0393 118.0 1180 3.8502 0.1372 0.1386 0.1372
3.9745 119.0 1190 3.8367 0.1381 0.1088 0.1381
3.967 120.0 1200 3.8276 0.1435 0.1360 0.1435
3.9181 121.0 1210 3.8158 0.1435 0.1202 0.1435
3.9061 122.0 1220 3.8048 0.1498 0.1190 0.1498
3.8693 123.0 1230 3.7884 0.1534 0.1379 0.1534
3.89 124.0 1240 3.7789 0.1516 0.1238 0.1516
3.9127 125.0 1250 3.7675 0.1534 0.1233 0.1534
3.8729 126.0 1260 3.7522 0.1579 0.1213 0.1579
3.8648 127.0 1270 3.7369 0.1588 0.1501 0.1588
3.8342 128.0 1280 3.7283 0.1715 0.1658 0.1715
3.8084 129.0 1290 3.7103 0.1769 0.1762 0.1769
3.7692 130.0 1300 3.6965 0.1787 0.1745 0.1787
3.909 131.0 1310 3.6818 0.1760 0.1753 0.1760
3.9092 132.0 1320 3.6709 0.1859 0.1799 0.1859
3.8076 133.0 1330 3.6574 0.1877 0.2000 0.1877
3.7301 134.0 1340 3.6411 0.1977 0.2015 0.1977
3.7447 135.0 1350 3.6284 0.2022 0.1984 0.2022
3.799 136.0 1360 3.6134 0.2058 0.2174 0.2058
3.8104 137.0 1370 3.6018 0.2112 0.1981 0.2112
3.7602 138.0 1380 3.5914 0.2184 0.2369 0.2184
3.7332 139.0 1390 3.5740 0.2184 0.2322 0.2184
3.6969 140.0 1400 3.5599 0.2166 0.2168 0.2166
3.6568 141.0 1410 3.5432 0.2310 0.2392 0.2310
3.6962 142.0 1420 3.5282 0.25 0.2640 0.25
3.793 143.0 1430 3.5103 0.2437 0.2484 0.2437
3.6609 144.0 1440 3.4972 0.2491 0.2652 0.2491
3.6566 145.0 1450 3.4881 0.2455 0.2474 0.2455
3.6383 146.0 1460 3.4677 0.2662 0.2903 0.2662
3.5767 147.0 1470 3.4536 0.2825 0.3205 0.2825
3.6348 148.0 1480 3.4345 0.2870 0.2981 0.2870
3.544 149.0 1490 3.4207 0.2942 0.3112 0.2942
3.5659 150.0 1500 3.4050 0.3005 0.3166 0.3005
3.4987 151.0 1510 3.3870 0.3114 0.3419 0.3114
3.4926 152.0 1520 3.3704 0.3204 0.3421 0.3204
3.5855 153.0 1530 3.3566 0.3186 0.3439 0.3186
3.5167 154.0 1540 3.3378 0.3249 0.3408 0.3249
3.4696 155.0 1550 3.3253 0.3285 0.3430 0.3285
3.5773 156.0 1560 3.3106 0.3384 0.3421 0.3384
3.4278 157.0 1570 3.2929 0.3321 0.3394 0.3321
3.4095 158.0 1580 3.2782 0.3502 0.3538 0.3502
3.4397 159.0 1590 3.2679 0.3457 0.3628 0.3457
3.4673 160.0 1600 3.2511 0.3520 0.3292 0.3520
3.4476 161.0 1610 3.2328 0.3601 0.3688 0.3601
3.437 162.0 1620 3.2180 0.3610 0.3537 0.3610
3.4093 163.0 1630 3.2026 0.3709 0.4053 0.3709
3.4577 164.0 1640 3.1883 0.3700 0.3897 0.3700
3.3099 165.0 1650 3.1736 0.3718 0.3832 0.3718
3.3388 166.0 1660 3.1631 0.3827 0.4179 0.3827
3.3541 167.0 1670 3.1446 0.3827 0.4012 0.3827
3.382 168.0 1680 3.1291 0.3989 0.4232 0.3989
3.2747 169.0 1690 3.1227 0.4043 0.4301 0.4043
3.4333 170.0 1700 3.1099 0.4224 0.4477 0.4224
3.3016 171.0 1710 3.0858 0.4134 0.4520 0.4134
3.215 172.0 1720 3.0741 0.4143 0.4504 0.4143
3.2936 173.0 1730 3.0564 0.4305 0.4788 0.4305
3.192 174.0 1740 3.0430 0.4377 0.4908 0.4377
3.2965 175.0 1750 3.0217 0.4422 0.4890 0.4422
3.2608 176.0 1760 3.0117 0.4522 0.4843 0.4522
3.2342 177.0 1770 2.9998 0.4495 0.5003 0.4495
3.1355 178.0 1780 2.9824 0.4558 0.4980 0.4558
3.2643 179.0 1790 2.9672 0.4621 0.5047 0.4621
3.1326 180.0 1800 2.9540 0.4666 0.5162 0.4666
3.1373 181.0 1810 2.9381 0.4666 0.5073 0.4666
3.1912 182.0 1820 2.9226 0.4657 0.5038 0.4657
3.0957 183.0 1830 2.9120 0.4774 0.5140 0.4774
3.2128 184.0 1840 2.8917 0.4765 0.5290 0.4765
3.2406 185.0 1850 2.8833 0.4838 0.5286 0.4838
3.0409 186.0 1860 2.8685 0.4847 0.5308 0.4847
3.0671 187.0 1870 2.8537 0.4982 0.5581 0.4982
3.0981 188.0 1880 2.8359 0.5018 0.5336 0.5018
3.0968 189.0 1890 2.8193 0.5135 0.5706 0.5135
3.0228 190.0 1900 2.8038 0.5099 0.5500 0.5099
2.9627 191.0 1910 2.7966 0.5108 0.5546 0.5108
2.9873 192.0 1920 2.7818 0.5144 0.5396 0.5144
3.0845 193.0 1930 2.7622 0.5289 0.5686 0.5289
3.0916 194.0 1940 2.7505 0.5325 0.5773 0.5325
2.8992 195.0 1950 2.7324 0.5334 0.5889 0.5334
2.8919 196.0 1960 2.7179 0.5406 0.5878 0.5406
2.9817 197.0 1970 2.7112 0.5343 0.5809 0.5343
2.855 198.0 1980 2.6864 0.5352 0.5920 0.5352
2.8388 199.0 1990 2.6790 0.5379 0.5949 0.5379
2.8402 200.0 2000 2.6587 0.5460 0.6041 0.5460
2.9817 201.0 2010 2.6489 0.5523 0.5944 0.5523
2.9825 202.0 2020 2.6333 0.5578 0.5915 0.5578
2.8034 203.0 2030 2.6221 0.5460 0.5980 0.5460
2.7729 204.0 2040 2.6040 0.5605 0.6132 0.5605
2.8668 205.0 2050 2.5889 0.5650 0.5978 0.5650
2.7692 206.0 2060 2.5755 0.5641 0.6120 0.5641
2.7259 207.0 2070 2.5617 0.5623 0.6047 0.5623
2.7308 208.0 2080 2.5483 0.5677 0.6150 0.5677
2.7992 209.0 2090 2.5416 0.5713 0.6279 0.5713
2.9132 210.0 2100 2.5311 0.5749 0.6200 0.5749
2.7445 211.0 2110 2.5195 0.5722 0.6158 0.5722
2.6778 212.0 2120 2.4984 0.5785 0.5916 0.5785
2.6307 213.0 2130 2.4827 0.5830 0.6148 0.5830
2.846 214.0 2140 2.4834 0.5758 0.6059 0.5758
2.7206 215.0 2150 2.4618 0.5957 0.6401 0.5957
2.7119 216.0 2160 2.4492 0.5975 0.6398 0.5975
2.795 217.0 2170 2.4389 0.5912 0.6206 0.5912
2.9871 218.0 2180 2.4156 0.6065 0.6591 0.6065
2.7607 219.0 2190 2.4093 0.6056 0.6387 0.6056
2.6345 220.0 2200 2.3989 0.6038 0.6576 0.6038
2.6909 221.0 2210 2.3842 0.6137 0.6456 0.6137
2.7537 222.0 2220 2.3700 0.6182 0.6464 0.6182
2.6008 223.0 2230 2.3615 0.6155 0.6422 0.6155
2.4937 224.0 2240 2.3518 0.6173 0.6393 0.6173
2.5116 225.0 2250 2.3296 0.6137 0.6396 0.6137
2.6128 226.0 2260 2.3168 0.6282 0.6558 0.6282
2.5334 227.0 2270 2.2998 0.6264 0.6439 0.6264
2.7573 228.0 2280 2.2866 0.6372 0.6564 0.6372
2.4452 229.0 2290 2.2771 0.6345 0.6628 0.6345
2.6947 230.0 2300 2.2697 0.6327 0.6593 0.6327
2.4291 231.0 2310 2.2491 0.6345 0.6577 0.6345
2.5337 232.0 2320 2.2446 0.6381 0.6433 0.6381
2.4177 233.0 2330 2.2234 0.6408 0.6558 0.6408
2.5558 234.0 2340 2.2191 0.6471 0.6714 0.6471
2.4394 235.0 2350 2.2081 0.6534 0.6791 0.6534
2.4154 236.0 2360 2.2054 0.6471 0.6681 0.6471
2.3774 237.0 2370 2.1779 0.6643 0.6798 0.6643
2.3426 238.0 2380 2.1709 0.6489 0.6761 0.6489
2.3236 239.0 2390 2.1557 0.6579 0.6676 0.6579
2.2995 240.0 2400 2.1449 0.6597 0.6674 0.6597
2.2818 241.0 2410 2.1271 0.6579 0.6671 0.6579
2.3765 242.0 2420 2.1125 0.6643 0.6792 0.6643
2.4038 243.0 2430 2.1010 0.6679 0.6770 0.6679
2.4796 244.0 2440 2.0854 0.6742 0.6873 0.6742
2.2569 245.0 2450 2.0759 0.6760 0.7034 0.6760
2.2851 246.0 2460 2.0813 0.6751 0.6953 0.6751
2.3342 247.0 2470 2.0555 0.6697 0.6917 0.6697
2.3354 248.0 2480 2.0475 0.6742 0.6929 0.6742
2.1678 249.0 2490 2.0294 0.6715 0.6858 0.6715
2.1957 250.0 2500 2.0184 0.6850 0.7021 0.6850
2.119 251.0 2510 2.0031 0.6922 0.7048 0.6922
2.1851 252.0 2520 1.9861 0.6904 0.7044 0.6904
2.2257 253.0 2530 1.9722 0.6859 0.6990 0.6859
2.123 254.0 2540 1.9605 0.6931 0.7165 0.6931
2.4325 255.0 2550 1.9596 0.6958 0.7162 0.6958
2.1362 256.0 2560 1.9444 0.6931 0.7237 0.6931
2.3492 257.0 2570 1.9362 0.6949 0.7126 0.6949
2.0604 258.0 2580 1.9136 0.7022 0.7279 0.7022
2.1024 259.0 2590 1.9246 0.6977 0.7246 0.6977
2.3549 260.0 2600 1.9055 0.6931 0.7216 0.6931
2.0618 261.0 2610 1.8942 0.6968 0.6999 0.6968
2.0736 262.0 2620 1.8897 0.6968 0.7049 0.6968
2.1983 263.0 2630 1.8704 0.7103 0.7227 0.7103
2.1957 264.0 2640 1.8787 0.7076 0.7311 0.7076
2.0086 265.0 2650 1.8497 0.7067 0.7310 0.7067
2.1341 266.0 2660 1.8425 0.7058 0.7234 0.7058
2.1557 267.0 2670 1.8351 0.7058 0.7336 0.7058
2.0351 268.0 2680 1.8163 0.7139 0.7219 0.7139
2.0577 269.0 2690 1.8077 0.7184 0.7442 0.7184
2.2401 270.0 2700 1.7902 0.7175 0.7347 0.7175
2.0027 271.0 2710 1.7876 0.7202 0.7371 0.7202
2.1012 272.0 2720 1.7793 0.7238 0.7409 0.7238
1.9428 273.0 2730 1.7743 0.7112 0.7360 0.7112
1.9601 274.0 2740 1.7559 0.7256 0.7381 0.7256
1.9504 275.0 2750 1.7601 0.7274 0.7390 0.7274
2.1852 276.0 2760 1.7449 0.7175 0.7438 0.7175
2.1266 277.0 2770 1.7272 0.7265 0.7387 0.7265
1.8728 278.0 2780 1.7222 0.7329 0.7490 0.7329
1.8193 279.0 2790 1.7016 0.7229 0.7384 0.7229
1.8423 280.0 2800 1.6950 0.7365 0.7513 0.7365
2.2335 281.0 2810 1.6807 0.7338 0.7520 0.7338
2.1217 282.0 2820 1.6837 0.7319 0.7373 0.7319
1.9901 283.0 2830 1.6730 0.7301 0.7452 0.7301
1.9524 284.0 2840 1.6582 0.7274 0.7517 0.7274
1.7966 285.0 2850 1.6520 0.7383 0.7565 0.7383
1.8229 286.0 2860 1.6435 0.7329 0.7369 0.7329
2.0777 287.0 2870 1.6288 0.7374 0.7452 0.7374
1.8964 288.0 2880 1.6143 0.7292 0.7487 0.7292
1.8628 289.0 2890 1.6064 0.7347 0.7453 0.7347
1.7922 290.0 2900 1.6049 0.7455 0.7744 0.7455
2.04 291.0 2910 1.5931 0.7392 0.7547 0.7392
1.7566 292.0 2920 1.5803 0.7392 0.7497 0.7392
1.7022 293.0 2930 1.5824 0.7473 0.7607 0.7473
1.6866 294.0 2940 1.5597 0.7446 0.7557 0.7446
1.7367 295.0 2950 1.5517 0.7319 0.7464 0.7319
1.8397 296.0 2960 1.5380 0.75 0.7652 0.75
1.669 297.0 2970 1.5302 0.7509 0.7615 0.7509
1.6794 298.0 2980 1.5320 0.7527 0.7621 0.7527
1.828 299.0 2990 1.5175 0.7419 0.7565 0.7419
1.7834 300.0 3000 1.5074 0.7509 0.7703 0.7509
1.6699 301.0 3010 1.5075 0.7473 0.7650 0.7473
1.7156 302.0 3020 1.4935 0.7509 0.7636 0.7509
1.8111 303.0 3030 1.4947 0.7401 0.7600 0.7401
1.7731 304.0 3040 1.4835 0.7617 0.7734 0.7617
1.5817 305.0 3050 1.4641 0.7509 0.7639 0.7509
1.6343 306.0 3060 1.4492 0.7581 0.7739 0.7581
1.8381 307.0 3070 1.4662 0.7635 0.7792 0.7635
1.7012 308.0 3080 1.4359 0.7545 0.7678 0.7545
1.8763 309.0 3090 1.4444 0.7554 0.7663 0.7554
1.5793 310.0 3100 1.4320 0.7554 0.7678 0.7554
1.5603 311.0 3110 1.4225 0.7518 0.7603 0.7518
1.7741 312.0 3120 1.4131 0.75 0.7691 0.75
1.5766 313.0 3130 1.4080 0.7518 0.7683 0.7518
1.4736 314.0 3140 1.3941 0.7581 0.7673 0.7581
1.6264 315.0 3150 1.3914 0.7644 0.7780 0.7644
1.7483 316.0 3160 1.3797 0.7608 0.7729 0.7608
1.6569 317.0 3170 1.3695 0.7590 0.7718 0.7590
1.5363 318.0 3180 1.3691 0.7662 0.7794 0.7662
1.8136 319.0 3190 1.3578 0.7635 0.7791 0.7635
1.7625 320.0 3200 1.3488 0.7581 0.7703 0.7581
1.6186 321.0 3210 1.3568 0.7527 0.7696 0.7527
1.8112 322.0 3220 1.3454 0.7545 0.7659 0.7545
1.4262 323.0 3230 1.3371 0.7644 0.7781 0.7644
1.4995 324.0 3240 1.3245 0.7635 0.7770 0.7635
1.6076 325.0 3250 1.3208 0.7644 0.7732 0.7644
1.5242 326.0 3260 1.3099 0.7717 0.7854 0.7717
1.5273 327.0 3270 1.3128 0.7599 0.7744 0.7599
1.4855 328.0 3280 1.3036 0.7644 0.7814 0.7644
1.4639 329.0 3290 1.2891 0.7690 0.7834 0.7690
1.8007 330.0 3300 1.2930 0.7717 0.7887 0.7717
1.8972 331.0 3310 1.2880 0.7671 0.7796 0.7671
1.5515 332.0 3320 1.3011 0.7635 0.7796 0.7635
1.6102 333.0 3330 1.2743 0.7681 0.7851 0.7681
1.8677 334.0 3340 1.2649 0.7708 0.7831 0.7708
1.9772 335.0 3350 1.2597 0.7699 0.7815 0.7699
1.5305 336.0 3360 1.2623 0.7662 0.7825 0.7662
1.8061 337.0 3370 1.2525 0.7780 0.7924 0.7780
1.5673 338.0 3380 1.2456 0.7653 0.7786 0.7653
1.3598 339.0 3390 1.2389 0.7744 0.7883 0.7744
1.326 340.0 3400 1.2214 0.7816 0.7934 0.7816
1.3974 341.0 3410 1.2267 0.7717 0.7847 0.7717
1.3891 342.0 3420 1.2119 0.7681 0.7777 0.7681
1.2873 343.0 3430 1.2019 0.7753 0.7904 0.7753
1.4346 344.0 3440 1.1926 0.7762 0.7867 0.7762
1.3439 345.0 3450 1.2067 0.7708 0.7862 0.7708
1.4577 346.0 3460 1.1838 0.7789 0.7880 0.7789
1.3218 347.0 3470 1.2042 0.7744 0.7931 0.7744
1.4273 348.0 3480 1.1722 0.7789 0.7931 0.7789
1.452 349.0 3490 1.1749 0.7653 0.7777 0.7653
1.3034 350.0 3500 1.1842 0.7762 0.7943 0.7762
1.4069 351.0 3510 1.1577 0.7753 0.7893 0.7753
1.2431 352.0 3520 1.1582 0.7825 0.7963 0.7825
1.499 353.0 3530 1.1665 0.7798 0.7933 0.7798
1.214 354.0 3540 1.1510 0.7744 0.7878 0.7744
1.1354 355.0 3550 1.1351 0.7888 0.8001 0.7888
1.2467 356.0 3560 1.1361 0.7753 0.7907 0.7753
1.3973 357.0 3570 1.1457 0.7753 0.7902 0.7753
1.3559 358.0 3580 1.1150 0.7825 0.7946 0.7825
1.3176 359.0 3590 1.1251 0.7825 0.7975 0.7825
1.3633 360.0 3600 1.1263 0.7753 0.7885 0.7753
1.128 361.0 3610 1.1133 0.7789 0.7932 0.7789
1.5197 362.0 3620 1.1116 0.7771 0.7919 0.7771
1.368 363.0 3630 1.1052 0.7825 0.7974 0.7825
1.0976 364.0 3640 1.0831 0.7807 0.7923 0.7807
1.3359 365.0 3650 1.0960 0.7798 0.7978 0.7798
1.3886 366.0 3660 1.0849 0.7762 0.7895 0.7762
1.125 367.0 3670 1.0962 0.7816 0.7900 0.7816
1.4953 368.0 3680 1.0768 0.7789 0.7947 0.7789
1.042 369.0 3690 1.0785 0.7807 0.7942 0.7807
1.3528 370.0 3700 1.0859 0.7771 0.7881 0.7771
1.2932 371.0 3710 1.0760 0.7807 0.7959 0.7807
1.0688 372.0 3720 1.0624 0.7825 0.7900 0.7825
1.3328 373.0 3730 1.0468 0.7897 0.7985 0.7897
1.1698 374.0 3740 1.0593 0.7762 0.7921 0.7762
1.287 375.0 3750 1.0427 0.7807 0.7895 0.7807
1.32 376.0 3760 1.0645 0.7780 0.7962 0.7780
1.1635 377.0 3770 1.0564 0.7843 0.7979 0.7843
1.648 378.0 3780 1.0435 0.7744 0.7845 0.7744
1.5143 379.0 3790 1.0389 0.7888 0.8023 0.7888
1.4117 380.0 3800 1.0239 0.7888 0.8021 0.7888
0.9873 381.0 3810 1.0129 0.7897 0.8035 0.7897
1.4631 382.0 3820 1.0347 0.7852 0.7969 0.7852
1.0484 383.0 3830 1.0195 0.7888 0.7990 0.7888
1.3335 384.0 3840 1.0399 0.7780 0.7951 0.7780
1.0543 385.0 3850 1.0087 0.7852 0.8005 0.7852
1.1046 386.0 3860 1.0092 0.7861 0.8024 0.7861
1.1993 387.0 3870 1.0189 0.7834 0.7972 0.7834
1.1793 388.0 3880 1.0021 0.7852 0.7972 0.7852
1.3611 389.0 3890 0.9916 0.7933 0.8031 0.7933
1.1336 390.0 3900 0.9868 0.7888 0.7996 0.7888
1.0034 391.0 3910 0.9845 0.7852 0.7948 0.7852
1.2326 392.0 3920 0.9759 0.7924 0.8052 0.7924
1.0302 393.0 3930 0.9814 0.7888 0.7985 0.7888
1.5907 394.0 3940 0.9921 0.7834 0.7987 0.7834
0.9445 395.0 3950 0.9907 0.7816 0.7960 0.7816
1.124 396.0 3960 0.9724 0.7924 0.8045 0.7924
1.0577 397.0 3970 0.9724 0.7798 0.7922 0.7798
0.9603 398.0 3980 0.9580 0.7897 0.8021 0.7897
0.9769 399.0 3990 0.9640 0.7843 0.7941 0.7843
1.2528 400.0 4000 0.9670 0.7825 0.7943 0.7825
0.9628 401.0 4010 0.9671 0.7870 0.8007 0.7870
1.2348 402.0 4020 0.9471 0.7987 0.8091 0.7987
0.9567 403.0 4030 0.9555 0.7861 0.8010 0.7861
1.1199 404.0 4040 0.9467 0.7888 0.8035 0.7888
0.939 405.0 4050 0.9365 0.7969 0.8118 0.7969
1.3309 406.0 4060 0.9419 0.7870 0.8007 0.7870
1.0253 407.0 4070 0.9443 0.7906 0.8022 0.7906
0.9437 408.0 4080 0.9336 0.7852 0.8019 0.7852
1.1108 409.0 4090 0.9483 0.7888 0.8061 0.7888
0.7806 410.0 4100 0.9306 0.7888 0.8033 0.7888
1.3151 411.0 4110 0.9370 0.7852 0.7953 0.7852
1.123 412.0 4120 0.9312 0.7915 0.8050 0.7915
0.9798 413.0 4130 0.9223 0.7843 0.8001 0.7843
0.8806 414.0 4140 0.9188 0.7870 0.7988 0.7870
0.8817 415.0 4150 0.9037 0.8042 0.8173 0.8042
1.1249 416.0 4160 0.9076 0.7969 0.8096 0.7969
1.279 417.0 4170 0.9028 0.7978 0.8099 0.7978
1.2903 418.0 4180 0.8964 0.7951 0.8090 0.7951
1.1344 419.0 4190 0.9044 0.7942 0.8100 0.7942
0.846 420.0 4200 0.9019 0.7915 0.8050 0.7915
0.8546 421.0 4210 0.8786 0.8032 0.8178 0.8032
0.9682 422.0 4220 0.8994 0.7960 0.8141 0.7960
0.877 423.0 4230 0.9019 0.7906 0.7996 0.7906
0.8649 424.0 4240 0.8832 0.7951 0.8057 0.7951
0.9264 425.0 4250 0.8952 0.7942 0.8130 0.7942
1.0808 426.0 4260 0.8835 0.7960 0.8112 0.7960

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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