update model card README.md
Browse files
README.md
CHANGED
|
@@ -13,7 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 13 |
|
| 14 |
This model is a fine-tuned version of [mgh6/esm_cluster_35M_linear](https://huggingface.co/mgh6/esm_cluster_35M_linear) on the None dataset.
|
| 15 |
It achieves the following results on the evaluation set:
|
| 16 |
-
- Loss: 0.
|
| 17 |
|
| 18 |
## Model description
|
| 19 |
|
|
@@ -44,65 +44,65 @@ The following hyperparameters were used during training:
|
|
| 44 |
|
| 45 |
| Training Loss | Epoch | Step | Validation Loss |
|
| 46 |
|:-------------:|:-----:|:----:|:---------------:|
|
| 47 |
-
| 0.
|
| 48 |
-
| 0.
|
| 49 |
-
| 0.
|
| 50 |
-
| 0.
|
| 51 |
-
| 0.
|
| 52 |
-
| 0.
|
| 53 |
-
| 0.
|
| 54 |
-
| 0.
|
| 55 |
-
| 0.
|
| 56 |
-
| 0.
|
| 57 |
-
| 0.
|
| 58 |
-
| 0.
|
| 59 |
-
| 0.
|
| 60 |
-
| 0.
|
| 61 |
-
| 0.
|
| 62 |
-
| 0.
|
| 63 |
-
| 0.
|
| 64 |
-
| 0.
|
| 65 |
-
| 0.
|
| 66 |
-
| 0.
|
| 67 |
-
| 0.
|
| 68 |
-
| 0.
|
| 69 |
-
| 0.
|
| 70 |
-
| 0.
|
| 71 |
-
| 0.
|
| 72 |
-
| 0.
|
| 73 |
-
| 0.
|
| 74 |
-
| 0.
|
| 75 |
-
| 0.
|
| 76 |
-
| 0.
|
| 77 |
-
| 0.
|
| 78 |
-
| 0.
|
| 79 |
-
| 0.
|
| 80 |
-
| 0.
|
| 81 |
-
| 0.
|
| 82 |
-
| 0.
|
| 83 |
-
| 0.
|
| 84 |
-
| 0.
|
| 85 |
-
| 0.
|
| 86 |
-
| 0.
|
| 87 |
-
| 0.
|
| 88 |
-
| 0.
|
| 89 |
-
| 0.
|
| 90 |
-
| 0.
|
| 91 |
-
| 0.
|
| 92 |
-
| 0.0072 | 6.17 | 4600 | 0.
|
| 93 |
-
| 0.
|
| 94 |
-
| 0.
|
| 95 |
-
| 0.
|
| 96 |
-
| 0.
|
| 97 |
-
| 0.0062 | 6.85 | 5100 | 0.
|
| 98 |
-
| 0.
|
| 99 |
-
| 0.
|
| 100 |
-
| 0.
|
| 101 |
-
| 0.
|
| 102 |
-
| 0.0033 | 7.52 | 5600 | 0.
|
| 103 |
-
| 0.
|
| 104 |
-
| 0.
|
| 105 |
-
| 0.
|
| 106 |
|
| 107 |
|
| 108 |
### Framework versions
|
|
|
|
| 13 |
|
| 14 |
This model is a fine-tuned version of [mgh6/esm_cluster_35M_linear](https://huggingface.co/mgh6/esm_cluster_35M_linear) on the None dataset.
|
| 15 |
It achieves the following results on the evaluation set:
|
| 16 |
+
- Loss: 0.1515
|
| 17 |
|
| 18 |
## Model description
|
| 19 |
|
|
|
|
| 44 |
|
| 45 |
| Training Loss | Epoch | Step | Validation Loss |
|
| 46 |
|:-------------:|:-----:|:----:|:---------------:|
|
| 47 |
+
| 0.1694 | 0.13 | 100 | 0.1876 |
|
| 48 |
+
| 0.1104 | 0.27 | 200 | 0.1856 |
|
| 49 |
+
| 0.0976 | 0.4 | 300 | 0.2082 |
|
| 50 |
+
| 0.0858 | 0.54 | 400 | 0.1908 |
|
| 51 |
+
| 0.0832 | 0.67 | 500 | 0.1575 |
|
| 52 |
+
| 0.0853 | 0.81 | 600 | 0.1549 |
|
| 53 |
+
| 0.0788 | 0.94 | 700 | 0.1598 |
|
| 54 |
+
| 0.0629 | 1.07 | 800 | 0.1386 |
|
| 55 |
+
| 0.0579 | 1.21 | 900 | 0.2071 |
|
| 56 |
+
| 0.0571 | 1.34 | 1000 | 0.1667 |
|
| 57 |
+
| 0.0567 | 1.48 | 1100 | 0.1421 |
|
| 58 |
+
| 0.0527 | 1.61 | 1200 | 0.1623 |
|
| 59 |
+
| 0.0553 | 1.74 | 1300 | 0.1827 |
|
| 60 |
+
| 0.0557 | 1.88 | 1400 | 0.1535 |
|
| 61 |
+
| 0.0523 | 2.01 | 1500 | 0.1353 |
|
| 62 |
+
| 0.0358 | 2.15 | 1600 | 0.1409 |
|
| 63 |
+
| 0.041 | 2.28 | 1700 | 0.1502 |
|
| 64 |
+
| 0.042 | 2.42 | 1800 | 0.1427 |
|
| 65 |
+
| 0.04 | 2.55 | 1900 | 0.1505 |
|
| 66 |
+
| 0.04 | 2.68 | 2000 | 0.1366 |
|
| 67 |
+
| 0.0392 | 2.82 | 2100 | 0.1236 |
|
| 68 |
+
| 0.0409 | 2.95 | 2200 | 0.1210 |
|
| 69 |
+
| 0.0327 | 3.09 | 2300 | 0.1448 |
|
| 70 |
+
| 0.0293 | 3.22 | 2400 | 0.1535 |
|
| 71 |
+
| 0.0265 | 3.36 | 2500 | 0.1529 |
|
| 72 |
+
| 0.0268 | 3.49 | 2600 | 0.1557 |
|
| 73 |
+
| 0.0241 | 3.62 | 2700 | 0.1505 |
|
| 74 |
+
| 0.0264 | 3.76 | 2800 | 0.1447 |
|
| 75 |
+
| 0.0286 | 3.89 | 2900 | 0.1442 |
|
| 76 |
+
| 0.0306 | 4.03 | 3000 | 0.1504 |
|
| 77 |
+
| 0.0152 | 4.16 | 3100 | 0.1311 |
|
| 78 |
+
| 0.0185 | 4.3 | 3200 | 0.1873 |
|
| 79 |
+
| 0.0212 | 4.43 | 3300 | 0.1396 |
|
| 80 |
+
| 0.022 | 4.56 | 3400 | 0.1663 |
|
| 81 |
+
| 0.0206 | 4.7 | 3500 | 0.1443 |
|
| 82 |
+
| 0.0231 | 4.83 | 3600 | 0.1483 |
|
| 83 |
+
| 0.0172 | 4.97 | 3700 | 0.1413 |
|
| 84 |
+
| 0.0134 | 5.1 | 3800 | 0.1472 |
|
| 85 |
+
| 0.0129 | 5.23 | 3900 | 0.1442 |
|
| 86 |
+
| 0.0126 | 5.37 | 4000 | 0.1369 |
|
| 87 |
+
| 0.013 | 5.5 | 4100 | 0.1576 |
|
| 88 |
+
| 0.012 | 5.64 | 4200 | 0.1348 |
|
| 89 |
+
| 0.013 | 5.77 | 4300 | 0.1572 |
|
| 90 |
+
| 0.0123 | 5.91 | 4400 | 0.1529 |
|
| 91 |
+
| 0.0099 | 6.04 | 4500 | 0.1425 |
|
| 92 |
+
| 0.0072 | 6.17 | 4600 | 0.1540 |
|
| 93 |
+
| 0.0081 | 6.31 | 4700 | 0.1463 |
|
| 94 |
+
| 0.0075 | 6.44 | 4800 | 0.1540 |
|
| 95 |
+
| 0.0078 | 6.58 | 4900 | 0.1418 |
|
| 96 |
+
| 0.0062 | 6.71 | 5000 | 0.1640 |
|
| 97 |
+
| 0.0062 | 6.85 | 5100 | 0.1392 |
|
| 98 |
+
| 0.0068 | 6.98 | 5200 | 0.1572 |
|
| 99 |
+
| 0.0054 | 7.11 | 5300 | 0.1485 |
|
| 100 |
+
| 0.0046 | 7.25 | 5400 | 0.1445 |
|
| 101 |
+
| 0.0054 | 7.38 | 5500 | 0.1488 |
|
| 102 |
+
| 0.0033 | 7.52 | 5600 | 0.1478 |
|
| 103 |
+
| 0.0041 | 7.65 | 5700 | 0.1514 |
|
| 104 |
+
| 0.0044 | 7.79 | 5800 | 0.1508 |
|
| 105 |
+
| 0.0025 | 7.92 | 5900 | 0.1515 |
|
| 106 |
|
| 107 |
|
| 108 |
### Framework versions
|