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fpadovani
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de_childes_30

Fill-Mask
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Safetensors
roberta
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@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 4.1942
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  ## Model description
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@@ -43,62 +43,61 @@ The following hyperparameters were used during training:
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 40000
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  - training_steps: 100000
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- - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-------:|:------:|:---------------:|
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- | No log | 1.5021 | 2000 | 7.0910 |
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- | 6.9957 | 3.0041 | 4000 | 5.8267 |
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- | 6.9957 | 4.5062 | 6000 | 5.4651 |
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- | 5.213 | 6.0083 | 8000 | 5.1717 |
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- | 5.213 | 7.5103 | 10000 | 4.9590 |
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- | 4.7279 | 9.0124 | 12000 | 4.7918 |
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- | 4.7279 | 10.5145 | 14000 | 4.6601 |
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- | 4.4214 | 12.0165 | 16000 | 4.5524 |
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- | 4.4214 | 13.5186 | 18000 | 4.4587 |
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- | 4.195 | 15.0207 | 20000 | 4.3684 |
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- | 4.195 | 16.5227 | 22000 | 4.2900 |
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- | 4.0109 | 18.0248 | 24000 | 4.2277 |
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- | 4.0109 | 19.5268 | 26000 | 4.1726 |
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- | 3.8596 | 21.0289 | 28000 | 4.1288 |
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- | 3.8596 | 22.5310 | 30000 | 4.0892 |
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- | 3.7326 | 24.0330 | 32000 | 4.0589 |
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- | 3.7326 | 25.5351 | 34000 | 4.0279 |
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- | 3.6241 | 27.0372 | 36000 | 4.0029 |
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- | 3.6241 | 28.5392 | 38000 | 3.9903 |
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- | 3.5294 | 30.0413 | 40000 | 3.9732 |
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- | 3.5294 | 31.5434 | 42000 | 3.9699 |
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- | 3.4361 | 33.0454 | 44000 | 3.9619 |
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- | 3.4361 | 34.5475 | 46000 | 3.9608 |
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- | 3.3449 | 36.0496 | 48000 | 3.9666 |
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- | 3.3449 | 37.5516 | 50000 | 3.9692 |
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- | 3.2664 | 39.0537 | 52000 | 3.9745 |
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- | 3.2664 | 40.5558 | 54000 | 3.9862 |
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- | 3.1963 | 42.0578 | 56000 | 3.9972 |
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- | 3.1963 | 43.5757 | 58000 | 4.0077 |
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- | 3.1346 | 45.0777 | 60000 | 4.0204 |
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- | 3.1346 | 46.5798 | 62000 | 4.0262 |
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- | 3.0792 | 48.0819 | 64000 | 4.0405 |
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- | 3.0792 | 49.5839 | 66000 | 4.0522 |
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- | 3.0286 | 51.0860 | 68000 | 4.0700 |
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- | 3.0286 | 52.5881 | 70000 | 4.0754 |
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- | 2.9835 | 54.0901 | 72000 | 4.0929 |
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- | 2.9835 | 55.5922 | 74000 | 4.1004 |
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- | 2.942 | 57.0943 | 76000 | 4.1144 |
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- | 2.942 | 58.5963 | 78000 | 4.1265 |
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- | 2.9043 | 60.0984 | 80000 | 4.1325 |
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- | 2.9043 | 61.6005 | 82000 | 4.1431 |
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- | 2.8693 | 63.1025 | 84000 | 4.1530 |
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- | 2.8693 | 64.6046 | 86000 | 4.1612 |
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- | 2.8393 | 66.1066 | 88000 | 4.1716 |
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- | 2.8393 | 67.6087 | 90000 | 4.1759 |
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- | 2.8118 | 69.1108 | 92000 | 4.1815 |
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- | 2.8118 | 70.6128 | 94000 | 4.1873 |
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- | 2.7874 | 72.1149 | 96000 | 4.1914 |
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- | 2.7874 | 73.6170 | 98000 | 4.1935 |
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- | 2.7676 | 75.1190 | 100000 | 4.1942 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.6056
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  ## Model description
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 40000
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  - training_steps: 100000
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-------:|:------:|:---------------:|
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+ | No log | 1.5021 | 2000 | 7.4721 |
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+ | 7.3851 | 3.0041 | 4000 | 6.4176 |
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+ | 7.3851 | 4.5062 | 6000 | 6.3026 |
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+ | 6.0706 | 6.0083 | 8000 | 6.2009 |
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+ | 6.0706 | 7.5103 | 10000 | 6.1058 |
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+ | 5.8733 | 9.0124 | 12000 | 6.0330 |
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+ | 5.8733 | 10.5145 | 14000 | 5.9681 |
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+ | 5.723 | 12.0165 | 16000 | 5.8789 |
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+ | 5.723 | 13.5186 | 18000 | 5.8198 |
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+ | 5.6127 | 15.0207 | 20000 | 5.8021 |
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+ | 5.6127 | 16.5227 | 22000 | 5.7662 |
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+ | 5.5325 | 18.0248 | 24000 | 5.7319 |
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+ | 5.5325 | 19.5268 | 26000 | 5.7032 |
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+ | 5.4632 | 21.0289 | 28000 | 5.7046 |
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+ | 5.4632 | 22.5310 | 30000 | 5.5708 |
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+ | 5.2633 | 24.0330 | 32000 | 4.9945 |
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+ | 5.2633 | 25.5351 | 34000 | 4.5232 |
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+ | 4.3386 | 27.0372 | 36000 | 4.1401 |
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+ | 4.3386 | 28.5392 | 38000 | 3.8578 |
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+ | 3.6823 | 30.0413 | 40000 | 3.6679 |
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+ | 3.6823 | 31.5434 | 42000 | 3.5397 |
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+ | 3.3424 | 33.0454 | 44000 | 3.4013 |
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+ | 3.3424 | 34.5475 | 46000 | 3.3154 |
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+ | 3.1266 | 36.0496 | 48000 | 3.2563 |
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+ | 3.1266 | 37.5516 | 50000 | 3.1665 |
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+ | 2.9693 | 39.0537 | 52000 | 3.1341 |
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+ | 2.9693 | 40.5558 | 54000 | 3.0564 |
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+ | 2.8544 | 42.0578 | 56000 | 3.0329 |
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+ | 2.8544 | 43.5599 | 58000 | 2.9552 |
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+ | 2.758 | 45.0620 | 60000 | 2.9492 |
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+ | 2.758 | 46.5640 | 62000 | 2.8937 |
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+ | 2.684 | 48.0661 | 64000 | 2.8662 |
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+ | 2.684 | 49.5682 | 66000 | 2.8495 |
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+ | 2.6223 | 51.0702 | 68000 | 2.8253 |
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+ | 2.6223 | 52.5723 | 70000 | 2.7846 |
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+ | 2.5704 | 54.0744 | 72000 | 2.7910 |
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+ | 2.5704 | 55.5764 | 74000 | 2.7503 |
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+ | 2.5235 | 57.0785 | 76000 | 2.7392 |
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+ | 2.5235 | 58.5805 | 78000 | 2.7223 |
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+ | 2.4865 | 60.0826 | 80000 | 2.7142 |
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+ | 2.4865 | 61.5847 | 82000 | 2.7068 |
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+ | 2.4549 | 63.0867 | 84000 | 2.7050 |
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+ | 2.4549 | 64.5888 | 86000 | 2.6745 |
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+ | 2.427 | 66.0909 | 88000 | 2.6638 |
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+ | 2.427 | 67.5929 | 90000 | 2.6596 |
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+ | 2.4092 | 69.0950 | 92000 | 2.6478 |
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+ | 2.4092 | 70.5971 | 94000 | 2.6531 |
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+ | 2.3873 | 72.0991 | 96000 | 2.6315 |
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+ | 2.3873 | 73.6012 | 98000 | 2.6405 |
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+ | 2.3734 | 75.1033 | 100000 | 2.6056 |
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  ### Framework versions