Downloads · 30 days
4
12% of all-time downloads
fpadovani/de_child_mlm_13_new
de_child_mlm_13_new is a fill-mask model from fpadovani. Use it when you need the model to fill a missing word. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
4
12% of all-time downloads
All-time downloads
33
Public
Parameters
14.9M
2 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors2 GB · 99%
From the Hugging Face model README
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.5021 | 2000 | 7.4988 |
| 7.3813 | 3.0041 | 4000 | 6.4258 |
| 7.3813 | 4.5062 | 6000 | 6.2791 |
| 6.066 | 6.0083 | 8000 | 6.1818 |
| 6.066 | 7.5103 | 10000 | 6.0889 |
| 5.8698 | 9.0124 | 12000 | 5.9988 |
| 5.8698 | 10.5145 | 14000 | 5.9568 |
| 5.7254 | 12.0165 | 16000 | 5.8851 |
| 5.7254 | 13.5186 | 18000 | 5.8346 |
| 5.6122 | 15.0207 | 20000 | 5.8228 |
| 5.6122 | 16.5227 | 22000 | 5.7907 |
| 5.5355 | 18.0248 | 24000 | 5.7285 |
| 5.5355 | 19.5268 | 26000 | 5.7120 |
| 5.4628 | 21.0289 | 28000 | 5.6979 |
| 5.4628 | 22.5310 | 30000 | 5.6628 |
| 5.3953 | 24.0330 | 32000 | 5.5406 |
| 5.3953 | 25.5351 | 34000 | 4.8930 |
| 4.7388 | 27.0372 | 36000 | 4.3974 |
| 4.7388 | 28.5392 | 38000 | 4.0301 |
| 3.8729 | 30.0413 | 40000 | 3.7983 |
| 3.8729 | 31.5434 | 42000 | 3.6406 |
| 3.4504 | 33.0454 | 44000 | 3.5116 |
| 3.4504 | 34.5475 | 46000 | 3.4095 |
| 3.2069 | 36.0496 | 48000 | 3.2996 |
| 3.2069 | 37.5516 | 50000 | 3.2492 |
| 3.0353 | 39.0537 | 52000 | 3.1838 |
| 3.0353 | 40.5558 | 54000 | 3.1331 |
| 2.9099 | 42.0578 | 56000 | 3.0655 |
| 2.9099 | 43.5599 | 58000 | 3.0243 |
| 2.8155 | 45.0620 | 60000 | 2.9921 |
| 2.8155 | 46.5640 | 62000 | 2.9371 |
| 2.7281 | 48.0661 | 64000 | 2.9211 |
| 2.7281 | 49.5682 | 66000 | 2.8839 |
| 2.6562 | 51.0702 | 68000 | 2.8595 |
| 2.6562 | 52.5723 | 70000 | 2.8351 |
| 2.6059 | 54.0744 | 72000 | 2.8211 |
| 2.6059 | 55.5764 | 74000 | 2.8136 |
| 2.5537 | 57.0785 | 76000 | 2.7967 |
| 2.5537 | 58.5805 | 78000 | 2.7570 |
| 2.5182 | 60.0826 | 80000 | 2.7480 |
| 2.5182 | 61.5847 | 82000 | 2.7331 |
| 2.4783 | 63.0867 | 84000 | 2.7255 |
| 2.4783 | 64.5888 | 86000 | 2.6844 |
| 2.4516 | 66.0909 | 88000 | 2.6831 |
| 2.4516 | 67.5929 | 90000 | 2.7005 |
| 2.4273 | 69.0950 | 92000 | 2.6712 |
| 2.4273 | 70.5971 | 94000 | 2.6602 |
| 2.4089 | 72.0991 | 96000 | 2.6616 |
| 2.4089 | 73.6012 | 98000 | 2.6513 |
| 2.3975 | 75.1033 | 100000 | 2.6587 |