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--- |
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license: cc-by-4.0 |
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base_model: deepset/roberta-base-squad2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- covid_qa_deepset |
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model-index: |
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- name: roberta-squad2-finetuned-covidQA |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# roberta-squad2-finetuned-covidQA |
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This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the covid_qa_deepset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2338 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 250 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.416 | 0.01 | 20 | 0.3362 | |
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| 0.4503 | 0.02 | 40 | 0.3012 | |
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| 0.1529 | 0.04 | 60 | 0.3735 | |
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| 0.408 | 0.05 | 80 | 0.2852 | |
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| 0.4379 | 0.06 | 100 | 0.2575 | |
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| 0.2443 | 0.07 | 120 | 0.2880 | |
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| 0.3613 | 0.08 | 140 | 0.3336 | |
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| 0.3116 | 0.09 | 160 | 0.2532 | |
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| 0.3361 | 0.11 | 180 | 0.2585 | |
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| 0.3336 | 0.12 | 200 | 0.2854 | |
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| 0.2891 | 0.13 | 220 | 0.2633 | |
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| 0.3262 | 0.14 | 240 | 0.2311 | |
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| 0.2053 | 0.15 | 260 | 0.4100 | |
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| 0.2583 | 0.16 | 280 | 0.2908 | |
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| 0.3646 | 0.18 | 300 | 0.2456 | |
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| 0.2798 | 0.19 | 320 | 0.2468 | |
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| 0.3079 | 0.2 | 340 | 0.2746 | |
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| 0.4007 | 0.21 | 360 | 0.2521 | |
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| 0.3548 | 0.22 | 380 | 0.2783 | |
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| 0.3401 | 0.23 | 400 | 0.2667 | |
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| 0.3405 | 0.25 | 420 | 0.2408 | |
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| 0.3658 | 0.26 | 440 | 0.2376 | |
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| 0.2781 | 0.27 | 460 | 0.2415 | |
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| 0.1905 | 0.28 | 480 | 0.2597 | |
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| 0.2666 | 0.29 | 500 | 0.2667 | |
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| 0.2164 | 0.3 | 520 | 0.2394 | |
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| 0.2155 | 0.32 | 540 | 0.2780 | |
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| 0.2676 | 0.33 | 560 | 0.2831 | |
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| 0.3552 | 0.34 | 580 | 0.2416 | |
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| 0.2934 | 0.35 | 600 | 0.2362 | |
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| 0.2138 | 0.36 | 620 | 0.2450 | |
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| 0.1169 | 0.38 | 640 | 0.2686 | |
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| 0.1815 | 0.39 | 660 | 0.2512 | |
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| 0.3577 | 0.4 | 680 | 0.2632 | |
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| 0.3298 | 0.41 | 700 | 0.2721 | |
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| 0.2624 | 0.42 | 720 | 0.2667 | |
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| 0.4011 | 0.43 | 740 | 0.2414 | |
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| 0.4041 | 0.45 | 760 | 0.2264 | |
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| 0.3107 | 0.46 | 780 | 0.2342 | |
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| 0.3036 | 0.47 | 800 | 0.2202 | |
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| 0.2474 | 0.48 | 820 | 0.2449 | |
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| 0.2889 | 0.49 | 840 | 0.2601 | |
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| 0.1131 | 0.5 | 860 | 0.3004 | |
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| 0.2039 | 0.52 | 880 | 0.2730 | |
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| 0.2916 | 0.53 | 900 | 0.2598 | |
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| 0.2649 | 0.54 | 920 | 0.2425 | |
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| 0.16 | 0.55 | 940 | 0.2319 | |
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| 0.1761 | 0.56 | 960 | 0.2365 | |
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| 0.4593 | 0.57 | 980 | 0.2300 | |
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| 0.3461 | 0.59 | 1000 | 0.2360 | |
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| 0.2248 | 0.6 | 1020 | 0.2354 | |
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| 0.3183 | 0.61 | 1040 | 0.2266 | |
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| 0.179 | 0.62 | 1060 | 0.2332 | |
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| 0.1995 | 0.63 | 1080 | 0.2321 | |
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| 0.2084 | 0.65 | 1100 | 0.2222 | |
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| 0.2419 | 0.66 | 1120 | 0.2307 | |
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| 0.3359 | 0.67 | 1140 | 0.2212 | |
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| 0.2263 | 0.68 | 1160 | 0.2300 | |
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| 0.2362 | 0.69 | 1180 | 0.2326 | |
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| 0.3108 | 0.7 | 1200 | 0.2410 | |
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| 0.3218 | 0.72 | 1220 | 0.2906 | |
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| 0.2954 | 0.73 | 1240 | 0.2518 | |
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| 0.2026 | 0.74 | 1260 | 0.2348 | |
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| 0.2149 | 0.75 | 1280 | 0.2338 | |
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| 0.1686 | 0.76 | 1300 | 0.2362 | |
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| 0.1928 | 0.77 | 1320 | 0.2308 | |
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| 0.3103 | 0.79 | 1340 | 0.2183 | |
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| 0.1686 | 0.8 | 1360 | 0.2521 | |
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| 0.1691 | 0.81 | 1380 | 0.2509 | |
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| 0.3721 | 0.82 | 1400 | 0.2239 | |
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| 0.3334 | 0.83 | 1420 | 0.2304 | |
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| 0.3117 | 0.84 | 1440 | 0.2185 | |
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| 0.267 | 0.86 | 1460 | 0.2142 | |
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| 0.2403 | 0.87 | 1480 | 0.2215 | |
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| 0.3576 | 0.88 | 1500 | 0.2158 | |
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| 0.2544 | 0.89 | 1520 | 0.2284 | |
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| 0.2935 | 0.9 | 1540 | 0.2241 | |
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| 0.2224 | 0.91 | 1560 | 0.2208 | |
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| 0.2615 | 0.93 | 1580 | 0.2194 | |
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| 0.1746 | 0.94 | 1600 | 0.2372 | |
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| 0.2313 | 0.95 | 1620 | 0.2381 | |
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| 0.1911 | 0.96 | 1640 | 0.2472 | |
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| 0.2399 | 0.97 | 1660 | 0.2483 | |
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| 0.2611 | 0.99 | 1680 | 0.2420 | |
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| 0.313 | 1.0 | 1700 | 0.2234 | |
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| 0.1456 | 1.01 | 1720 | 0.2327 | |
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| 0.172 | 1.02 | 1740 | 0.2298 | |
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| 0.2197 | 1.03 | 1760 | 0.2376 | |
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| 0.1991 | 1.04 | 1780 | 0.2483 | |
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| 0.1186 | 1.06 | 1800 | 0.2455 | |
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| 0.1417 | 1.07 | 1820 | 0.2493 | |
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| 0.2101 | 1.08 | 1840 | 0.2423 | |
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| 0.1564 | 1.09 | 1860 | 0.2467 | |
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| 0.1816 | 1.1 | 1880 | 0.2505 | |
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| 0.2034 | 1.11 | 1900 | 0.3005 | |
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| 0.2178 | 1.13 | 1920 | 0.2384 | |
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| 0.2895 | 1.14 | 1940 | 0.2602 | |
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| 0.1629 | 1.15 | 1960 | 0.2422 | |
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| 0.2443 | 1.16 | 1980 | 0.2294 | |
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| 0.1776 | 1.17 | 2000 | 0.2403 | |
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| 0.181 | 1.18 | 2020 | 0.2302 | |
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| 0.1757 | 1.2 | 2040 | 0.2273 | |
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| 0.1523 | 1.21 | 2060 | 0.2272 | |
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| 0.0763 | 1.22 | 2080 | 0.2422 | |
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| 0.1534 | 1.23 | 2100 | 0.2445 | |
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| 0.1994 | 1.24 | 2120 | 0.2487 | |
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| 0.1826 | 1.26 | 2140 | 0.2569 | |
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| 0.2475 | 1.27 | 2160 | 0.2389 | |
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| 0.1977 | 1.28 | 2180 | 0.2290 | |
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| 0.2891 | 1.29 | 2200 | 0.2395 | |
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| 0.2049 | 1.3 | 2220 | 0.2292 | |
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| 0.2526 | 1.31 | 2240 | 0.2410 | |
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| 0.2927 | 1.33 | 2260 | 0.2270 | |
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| 0.1325 | 1.34 | 2280 | 0.2566 | |
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| 0.1331 | 1.35 | 2300 | 0.2400 | |
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| 0.1198 | 1.36 | 2320 | 0.2416 | |
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| 0.1766 | 1.37 | 2340 | 0.2407 | |
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| 0.1698 | 1.38 | 2360 | 0.2398 | |
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| 0.1545 | 1.4 | 2380 | 0.2437 | |
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| 0.2406 | 1.41 | 2400 | 0.2587 | |
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| 0.2583 | 1.42 | 2420 | 0.2292 | |
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| 0.1562 | 1.43 | 2440 | 0.2374 | |
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| 0.2528 | 1.44 | 2460 | 0.2326 | |
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| 0.1665 | 1.45 | 2480 | 0.2366 | |
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| 0.1893 | 1.47 | 2500 | 0.2323 | |
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| 0.109 | 1.48 | 2520 | 0.2492 | |
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| 0.1385 | 1.49 | 2540 | 0.2418 | |
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| 0.1267 | 1.5 | 2560 | 0.2437 | |
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| 0.2004 | 1.51 | 2580 | 0.2393 | |
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| 0.1754 | 1.52 | 2600 | 0.2408 | |
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| 0.2147 | 1.54 | 2620 | 0.2355 | |
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| 0.1409 | 1.55 | 2640 | 0.2460 | |
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| 0.1409 | 1.56 | 2660 | 0.2406 | |
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| 0.1456 | 1.57 | 2680 | 0.2443 | |
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| 0.1926 | 1.58 | 2700 | 0.2385 | |
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| 0.1772 | 1.6 | 2720 | 0.2342 | |
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| 0.2147 | 1.61 | 2740 | 0.2346 | |
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| 0.2292 | 1.62 | 2760 | 0.2319 | |
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| 0.2335 | 1.63 | 2780 | 0.2303 | |
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| 0.1409 | 1.64 | 2800 | 0.2347 | |
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| 0.1004 | 1.65 | 2820 | 0.2502 | |
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| 0.281 | 1.67 | 2840 | 0.2296 | |
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| 0.1071 | 1.68 | 2860 | 0.2360 | |
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| 0.1152 | 1.69 | 2880 | 0.2402 | |
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| 0.219 | 1.7 | 2900 | 0.2350 | |
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| 0.1384 | 1.71 | 2920 | 0.2367 | |
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| 0.1792 | 1.72 | 2940 | 0.2351 | |
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| 0.1795 | 1.74 | 2960 | 0.2338 | |
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| 0.1554 | 1.75 | 2980 | 0.2373 | |
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| 0.1764 | 1.76 | 3000 | 0.2352 | |
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| 0.2362 | 1.77 | 3020 | 0.2337 | |
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| 0.1912 | 1.78 | 3040 | 0.2304 | |
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| 0.1202 | 1.79 | 3060 | 0.2313 | |
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| 0.146 | 1.81 | 3080 | 0.2327 | |
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| 0.2677 | 1.82 | 3100 | 0.2305 | |
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| 0.1919 | 1.83 | 3120 | 0.2331 | |
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| 0.1535 | 1.84 | 3140 | 0.2317 | |
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| 0.1032 | 1.85 | 3160 | 0.2341 | |
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| 0.0792 | 1.87 | 3180 | 0.2341 | |
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| 0.1419 | 1.88 | 3200 | 0.2355 | |
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| 0.1179 | 1.89 | 3220 | 0.2369 | |
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| 0.1948 | 1.9 | 3240 | 0.2363 | |
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| 0.1651 | 1.91 | 3260 | 0.2362 | |
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| 0.2293 | 1.92 | 3280 | 0.2351 | |
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| 0.1542 | 1.94 | 3300 | 0.2358 | |
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| 0.2852 | 1.95 | 3320 | 0.2347 | |
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| 0.0927 | 1.96 | 3340 | 0.2350 | |
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| 0.1746 | 1.97 | 3360 | 0.2337 | |
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| 0.0902 | 1.98 | 3380 | 0.2341 | |
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| 0.2275 | 1.99 | 3400 | 0.2338 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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