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amrisaurus/pretrained-m-bert-90
pretrained-m-bert-90 is a machine learning model from amrisaurus. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
probably proofread and complete it, then remove this comment. --
Downloads · 30 days
2
1% of all-time downloads
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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:
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 10.2413 | 10.9668 | 0 |
| 7.5814 | 10.9638 | 1 |
| 7.0095 | 11.3733 | 2 |
| 6.4352 | 11.5989 | 3 |
| 6.7137 | 11.4072 | 4 |
| 6.4383 | 11.8287 | 5 |
| 6.2223 | 12.0344 | 6 |
| 6.1759 | 11.6900 | 7 |
| 6.0764 | 11.7144 | 8 |
| 5.8802 | 12.1089 | 9 |
| 6.0159 | 12.3456 | 10 |
| 5.9254 | 12.7065 | 11 |
| 5.6652 | nan | 12 |
| 5.8185 | 12.8155 | 13 |
| 5.9185 | 12.7047 | 14 |
| 5.8418 | 12.7175 | 15 |
| 5.9122 | 12.5688 | 16 |
| 5.9698 | 12.5251 | 17 |
| 5.8286 | 12.7015 | 18 |
| 5.8807 | 13.2514 | 19 |
| 5.8330 | 12.8541 | 20 |
| 5.6456 | 13.4088 | 21 |
| 5.7257 | 13.5517 | 22 |
| 5.8854 | 12.8775 | 23 |
| 5.6770 | 13.6499 | 24 |
| 5.6026 | 13.9732 | 25 |
| 5.6651 | 13.0827 | 26 |
| 5.8888 | 13.1292 | 27 |
| 5.8123 | 12.8970 | 28 |
| 5.7525 | 13.3724 | 29 |
| 5.9020 | 13.5507 | 30 |
| 5.8642 | 13.3284 | 31 |
| 5.9329 | 13.7350 | 32 |
| 5.7728 | 13.3011 | 33 |
| 5.8297 | 13.6108 | 34 |
| 5.8118 | 13.3331 | 35 |
| 5.7382 | 13.7047 | 36 |
| 5.8061 | 13.8107 | 37 |
| 5.8423 | 13.4207 | 38 |
| 5.8442 | 13.6832 | 39 |
| 5.7680 | 14.1248 | 40 |
| 5.7668 | 13.6626 | 41 |
| 5.7826 | 13.6470 | 42 |
| 5.7692 | 13.9430 | 43 |
| 5.5109 | 14.0924 | 44 |
| 5.7394 | 14.0253 | 45 |
| 5.8013 | 13.5926 | 46 |
| 5.7222 | 13.9732 | 47 |
| 5.7023 | 14.0204 | 48 |
| 5.8250 | 13.9655 | 49 |
| 5.6064 | 14.0406 | 50 |
| 5.7319 | 14.1826 | 51 |
| 5.6849 | 13.9114 | 52 |
| 5.8167 | 13.9917 | 53 |
| 5.7573 | 14.1509 | 54 |
| 5.6921 | 14.3722 | 55 |
| 5.7190 | 14.4919 | 56 |
| 5.8501 | 13.6970 | 57 |
| 5.7627 | 14.1393 | 58 |
| 5.8031 | 14.1246 | 59 |
| 5.7207 | 14.3084 | 60 |
| 5.7979 | 13.9398 | 61 |
| 5.7068 | 14.2865 | 62 |
| 5.7547 | 14.2590 | 63 |
| 5.8349 | 14.1481 | 64 |
| 5.7924 | 14.0461 | 65 |
| 5.8127 | 14.1274 | 66 |
| 5.7590 | 14.3578 | 67 |
| 5.8297 | 14.2429 | 68 |
| 5.7822 | 14.2742 | 69 |
| 5.7708 | 14.3720 | 70 |
| 5.6521 | 14.8640 | 71 |
| 5.7253 | 14.4404 | 72 |
| 5.8076 | 14.1843 | 73 |
| 5.7746 | 14.4657 | 74 |
| 5.8592 | 14.2965 | 75 |
| 5.6643 | 14.0996 | 76 |
| 5.7849 | 14.3531 | 77 |
| 5.7418 | 14.4266 | 78 |
| 5.7030 | 14.5584 | 79 |
| 5.8298 | 14.1390 | 80 |
| 5.9061 | 13.9172 | 81 |
| 5.6570 | 14.6991 | 82 |
| 5.7040 | 14.7839 | 83 |
| 5.8064 | 14.2581 | 84 |
| 5.6855 | 14.4449 | 85 |
| 5.7803 | 14.7469 | 86 |
| 5.7495 | 14.4704 | 87 |
| 5.7539 | 14.5520 | 88 |
| 5.7094 | 14.5332 | 89 |