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fpadovani/en_child_mlm_42_new
en_child_mlm_42_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. --
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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 | 1.3952 | 2000 | 7.2330 |
| 7.1737 | 2.7904 | 4000 | 6.0562 |
| 7.1737 | 4.1856 | 6000 | 5.9019 |
| 5.7174 | 5.5807 | 8000 | 5.8269 |
| 5.7174 | 6.9759 | 10000 | 5.7285 |
| 5.5259 | 8.3711 | 12000 | 5.6720 |
| 5.5259 | 9.7663 | 14000 | 5.6001 |
| 5.3823 | 11.1615 | 16000 | 5.5332 |
| 5.3823 | 12.5567 | 18000 | 5.4909 |
| 5.2741 | 13.9519 | 20000 | 5.4375 |
| 5.2741 | 15.3471 | 22000 | 5.3855 |
| 5.1793 | 16.7422 | 24000 | 5.3575 |
| 5.1793 | 18.1374 | 26000 | 5.1495 |
| 4.9507 | 19.5326 | 28000 | 4.8875 |
| 4.9507 | 20.9278 | 30000 | 4.2745 |
| 4.2004 | 22.3230 | 32000 | 3.7086 |
| 4.2004 | 23.7182 | 34000 | 3.3358 |
| 3.2217 | 25.1134 | 36000 | 3.1451 |
| 3.2217 | 26.5085 | 38000 | 3.0074 |
| 2.8512 | 27.9037 | 40000 | 2.9096 |
| 2.8512 | 29.2989 | 42000 | 2.8026 |
| 2.6434 | 30.6941 | 44000 | 2.7181 |
| 2.6434 | 32.0893 | 46000 | 2.6473 |
| 2.493 | 33.4845 | 48000 | 2.6064 |
| 2.493 | 34.8797 | 50000 | 2.5506 |
| 2.3811 | 36.2749 | 52000 | 2.5127 |
| 2.3811 | 37.6700 | 54000 | 2.4719 |
| 2.2923 | 39.0652 | 56000 | 2.4635 |
| 2.2923 | 40.4604 | 58000 | 2.3898 |
| 2.2233 | 41.8556 | 60000 | 2.3851 |
| 2.2233 | 43.2508 | 62000 | 2.3598 |
| 2.1648 | 44.6460 | 64000 | 2.3266 |
| 2.1648 | 46.0412 | 66000 | 2.3263 |
| 2.1174 | 47.4363 | 68000 | 2.2709 |
| 2.1174 | 48.8315 | 70000 | 2.2813 |
| 2.0796 | 50.2267 | 72000 | 2.2491 |
| 2.0796 | 51.6219 | 74000 | 2.2636 |
| 2.0437 | 53.0171 | 76000 | 2.2123 |
| 2.0437 | 54.4308 | 78000 | 2.2143 |
| 2.0093 | 55.8260 | 80000 | 2.2034 |
| 2.0093 | 57.2211 | 82000 | 2.1941 |
| 1.9808 | 58.6163 | 84000 | 2.1837 |
| 1.9808 | 60.0115 | 86000 | 2.1810 |
| 1.9618 | 61.4067 | 88000 | 2.1704 |
| 1.9618 | 62.8019 | 90000 | 2.1641 |
| 1.9425 | 64.1971 | 92000 | 2.1218 |
| 1.9425 | 65.5923 | 94000 | 2.1356 |
| 1.9254 | 66.9874 | 96000 | 2.1605 |
| 1.9254 | 68.3826 | 98000 | 2.1212 |
| 1.9141 | 69.7778 | 100000 | 2.1418 |