End of training
Browse files- README.md +159 -57
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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This model is a fine-tuned version of [adalbertojunior/distilbert-portuguese-cased](https://huggingface.co/adalbertojunior/distilbert-portuguese-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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### Training results
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### Framework versions
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This model is a fine-tuned version of [adalbertojunior/distilbert-portuguese-cased](https://huggingface.co/adalbertojunior/distilbert-portuguese-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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+
- Loss: 0.7396
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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| 49 |
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|:-------------:|:--------:|:-----:|:---------------:|
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| 50 |
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| 6.7563 | 1.6949 | 100 | 5.4137 |
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| 51 |
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| 5.0553 | 3.3898 | 200 | 4.4824 |
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| 52 |
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| 4.3687 | 5.0847 | 300 | 3.9332 |
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| 53 |
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| 3.9319 | 6.7797 | 400 | 3.5644 |
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| 3.6101 | 8.4746 | 500 | 3.2889 |
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| 3.3843 | 10.1695 | 600 | 3.0760 |
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| 3.1869 | 11.8644 | 700 | 2.9195 |
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| 3.0395 | 13.5593 | 800 | 2.7842 |
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| 2.9038 | 15.2542 | 900 | 2.6563 |
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| 2.7768 | 16.9492 | 1000 | 2.5554 |
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| 2.6835 | 18.6441 | 1100 | 2.4614 |
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| 2.5903 | 20.3390 | 1200 | 2.3882 |
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| 2.5214 | 22.0339 | 1300 | 2.3210 |
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| 2.4401 | 23.7288 | 1400 | 2.2352 |
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| 2.373 | 25.4237 | 1500 | 2.2145 |
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| 2.3147 | 27.1186 | 1600 | 2.1609 |
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| 2.2606 | 28.8136 | 1700 | 2.0704 |
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| 2.2064 | 30.5085 | 1800 | 2.0260 |
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| 2.1572 | 32.2034 | 1900 | 2.0259 |
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| 2.1258 | 33.8983 | 2000 | 1.9498 |
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| 2.0683 | 35.5932 | 2100 | 1.9212 |
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| 2.0374 | 37.2881 | 2200 | 1.8884 |
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| 1.9998 | 38.9831 | 2300 | 1.8543 |
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| 1.9582 | 40.6780 | 2400 | 1.8106 |
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| 1.932 | 42.3729 | 2500 | 1.7822 |
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| 1.8862 | 44.0678 | 2600 | 1.7673 |
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| 1.8677 | 45.7627 | 2700 | 1.7280 |
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| 1.8375 | 47.4576 | 2800 | 1.7147 |
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| 1.8128 | 49.1525 | 2900 | 1.6882 |
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| 1.7874 | 50.8475 | 3000 | 1.6357 |
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| 1.7628 | 52.5424 | 3100 | 1.6502 |
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| 1.7391 | 54.2373 | 3200 | 1.6312 |
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| 1.709 | 55.9322 | 3300 | 1.5989 |
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| 1.6878 | 57.6271 | 3400 | 1.5503 |
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| 1.6605 | 59.3220 | 3500 | 1.5602 |
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| 1.6331 | 61.0169 | 3600 | 1.5486 |
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| 1.6206 | 62.7119 | 3700 | 1.5046 |
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| 1.6057 | 64.4068 | 3800 | 1.5098 |
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| 1.5877 | 66.1017 | 3900 | 1.4885 |
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| 1.5576 | 67.7966 | 4000 | 1.4747 |
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| 1.5413 | 69.4915 | 4100 | 1.4500 |
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| 1.5142 | 71.1864 | 4200 | 1.3917 |
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| 1.4847 | 72.8814 | 4300 | 1.3771 |
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| 1.4665 | 74.5763 | 4400 | 1.3737 |
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| 1.4562 | 76.2712 | 4500 | 1.3560 |
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| 1.4422 | 77.9661 | 4600 | 1.3394 |
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| 1.4148 | 79.6610 | 4700 | 1.3453 |
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| 1.4108 | 81.3559 | 4800 | 1.3261 |
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| 1.3992 | 83.0508 | 4900 | 1.3111 |
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| 1.3784 | 84.7458 | 5000 | 1.3083 |
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| 1.3607 | 86.4407 | 5100 | 1.2982 |
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| 1.352 | 88.1356 | 5200 | 1.2758 |
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| 1.3353 | 89.8305 | 5300 | 1.2818 |
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| 1.3173 | 91.5254 | 5400 | 1.2697 |
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| 1.3085 | 93.2203 | 5500 | 1.2440 |
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| 1.2955 | 94.9153 | 5600 | 1.2099 |
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| 1.2933 | 96.6102 | 5700 | 1.2337 |
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| 1.2757 | 98.3051 | 5800 | 1.2056 |
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| 1.262 | 100.0 | 5900 | 1.1993 |
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| 1.2509 | 101.6949 | 6000 | 1.1933 |
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| 1.2418 | 103.3898 | 6100 | 1.1645 |
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| 1.2275 | 105.0847 | 6200 | 1.1820 |
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| 1.2219 | 106.7797 | 6300 | 1.1452 |
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| 1.216 | 108.4746 | 6400 | 1.1709 |
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| 1.1954 | 110.1695 | 6500 | 1.1386 |
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| 1.1858 | 111.8644 | 6600 | 1.1336 |
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| 1.1799 | 113.5593 | 6700 | 1.1217 |
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| 1.1707 | 115.2542 | 6800 | 1.1102 |
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| 1.1653 | 116.9492 | 6900 | 1.1093 |
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| 1.1476 | 118.6441 | 7000 | 1.1032 |
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| 1.1406 | 120.3390 | 7100 | 1.1004 |
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| 1.1364 | 122.0339 | 7200 | 1.0698 |
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| 1.1173 | 123.7288 | 7300 | 1.0817 |
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| 1.1129 | 125.4237 | 7400 | 1.0825 |
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| 1.1077 | 127.1186 | 7500 | 1.0728 |
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| 1.0943 | 128.8136 | 7600 | 1.0496 |
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| 1.0881 | 130.5085 | 7700 | 1.0443 |
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| 1.0774 | 132.2034 | 7800 | 1.0392 |
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| 1.0789 | 133.8983 | 7900 | 1.0470 |
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| 1.0608 | 135.5932 | 8000 | 1.0248 |
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| 1.0516 | 137.2881 | 8100 | 1.0144 |
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| 1.0533 | 138.9831 | 8200 | 1.0246 |
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| 1.0401 | 140.6780 | 8300 | 1.0180 |
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| 1.0347 | 142.3729 | 8400 | 0.9903 |
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| 1.0268 | 144.0678 | 8500 | 0.9809 |
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| 1.016 | 145.7627 | 8600 | 0.9839 |
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| 1.003 | 147.4576 | 8700 | 0.9870 |
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| 1.0066 | 149.1525 | 8800 | 0.9610 |
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| 1.004 | 150.8475 | 8900 | 0.9488 |
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| 0.9918 | 152.5424 | 9000 | 0.9601 |
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| 0.996 | 154.2373 | 9100 | 0.9660 |
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| 0.9835 | 155.9322 | 9200 | 0.9376 |
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| 0.9801 | 157.6271 | 9300 | 0.9504 |
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| 0.9606 | 159.3220 | 9400 | 0.9482 |
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| 0.9646 | 161.0169 | 9500 | 0.9312 |
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| 0.9637 | 162.7119 | 9600 | 0.9304 |
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| 0.9528 | 164.4068 | 9700 | 0.9270 |
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| 0.9432 | 166.1017 | 9800 | 0.9205 |
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| 0.9398 | 167.7966 | 9900 | 0.9202 |
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| 0.9377 | 169.4915 | 10000 | 0.9167 |
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| 0.9282 | 171.1864 | 10100 | 0.9122 |
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| 0.9118 | 172.8814 | 10200 | 0.9034 |
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| 0.907 | 174.5763 | 10300 | 0.8839 |
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| 0.9152 | 176.2712 | 10400 | 0.8879 |
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| 0.9124 | 177.9661 | 10500 | 0.8885 |
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| 0.9005 | 179.6610 | 10600 | 0.8832 |
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| 0.8979 | 181.3559 | 10700 | 0.8767 |
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| 0.8836 | 183.0508 | 10800 | 0.8886 |
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| 0.882 | 184.7458 | 10900 | 0.8601 |
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| 0.8818 | 186.4407 | 11000 | 0.8713 |
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| 0.8724 | 188.1356 | 11100 | 0.8602 |
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| 0.8688 | 189.8305 | 11200 | 0.8510 |
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| 0.8677 | 191.5254 | 11300 | 0.8401 |
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| 0.8643 | 193.2203 | 11400 | 0.8453 |
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| 0.8638 | 194.9153 | 11500 | 0.8351 |
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| 0.8539 | 196.6102 | 11600 | 0.8460 |
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| 0.852 | 198.3051 | 11700 | 0.8474 |
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| 0.8433 | 200.0 | 11800 | 0.8249 |
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| 0.8394 | 201.6949 | 11900 | 0.8326 |
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| 0.8339 | 203.3898 | 12000 | 0.8331 |
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| 0.8284 | 205.0847 | 12100 | 0.8216 |
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| 0.8284 | 206.7797 | 12200 | 0.8148 |
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| 0.8261 | 208.4746 | 12300 | 0.8020 |
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| 0.8158 | 210.1695 | 12400 | 0.8112 |
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| 0.8148 | 211.8644 | 12500 | 0.8154 |
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| 0.8118 | 213.5593 | 12600 | 0.8058 |
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| 0.8067 | 215.2542 | 12700 | 0.8005 |
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| 0.8022 | 216.9492 | 12800 | 0.8021 |
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| 0.793 | 218.6441 | 12900 | 0.8000 |
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| 0.8003 | 220.3390 | 13000 | 0.7924 |
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| 0.7891 | 222.0339 | 13100 | 0.7891 |
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| 0.7802 | 223.7288 | 13200 | 0.7678 |
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| 0.7906 | 225.4237 | 13300 | 0.7902 |
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| 0.7756 | 227.1186 | 13400 | 0.7774 |
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| 0.7788 | 228.8136 | 13500 | 0.7639 |
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| 0.7654 | 230.5085 | 13600 | 0.7767 |
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| 0.7686 | 232.2034 | 13700 | 0.7831 |
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| 0.7691 | 233.8983 | 13800 | 0.7735 |
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| 0.7656 | 235.5932 | 13900 | 0.7632 |
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| 0.7597 | 237.2881 | 14000 | 0.7694 |
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| 0.7562 | 238.9831 | 14100 | 0.7475 |
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| 0.754 | 240.6780 | 14200 | 0.7585 |
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| 0.7461 | 242.3729 | 14300 | 0.7502 |
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| 0.749 | 244.0678 | 14400 | 0.7533 |
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| 0.7482 | 245.7627 | 14500 | 0.7308 |
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| 0.7436 | 247.4576 | 14600 | 0.7581 |
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| 0.7395 | 249.1525 | 14700 | 0.7118 |
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| 0.7339 | 250.8475 | 14800 | 0.7458 |
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| 0.7337 | 252.5424 | 14900 | 0.7232 |
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| 0.7262 | 254.2373 | 15000 | 0.7421 |
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| 0.7313 | 255.9322 | 15100 | 0.7097 |
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| 0.7223 | 257.6271 | 15200 | 0.7235 |
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| 0.7189 | 259.3220 | 15300 | 0.7222 |
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| 0.7228 | 261.0169 | 15400 | 0.7373 |
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| 0.7163 | 262.7119 | 15500 | 0.7247 |
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| 0.7102 | 264.4068 | 15600 | 0.7255 |
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### Framework versions
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 265721304
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version https://git-lfs.github.com/spec/v1
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size 265721304
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 5240
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version https://git-lfs.github.com/spec/v1
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oid sha256:b665a1bf51abfeac066e530b1a26e87df0501d84d6b8facff0975c1317d4c68c
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size 5240
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