update model card README.md

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Spearmanr
       type: spearmanr
-      value: 0.23980333080780145
+      value: 0.5742059850477367
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,8 +29,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [thundaa/tape-fluorescence-evotuning-DistilProtBert](https://huggingface.co/thundaa/tape-fluorescence-evotuning-DistilProtBert) on the cradle-bio/tape-fluorescence dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6838
-- Spearmanr: 0.2398
+- Loss: 0.2709
+- Spearmanr: 0.5742
 
 ## Model description
 
@@ -50,25 +50,50 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 32
-- eval_batch_size: 32
-- seed: 42
-- gradient_accumulation_steps: 128
-- total_train_batch_size: 4096
+- train_batch_size: 40
+- eval_batch_size: 40
+- seed: 11
+- gradient_accumulation_steps: 64
+- total_train_batch_size: 2560
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 30
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Spearmanr |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|
-| 9.0167        | 0.85  | 4    | 4.9224          | -0.0084   |
-| 4.0263        | 1.85  | 8    | 2.0909          | 0.0824    |
-| 1.7616        | 2.85  | 12   | 0.9869          | 0.1583    |
-| 0.9814        | 3.85  | 16   | 0.7071          | 0.2798    |
-| 0.7082        | 4.85  | 20   | 0.6838          | 0.2398    |
+| 6.4382        | 0.93  | 7    | 2.0198          | -0.0244   |
+| 1.1243        | 1.93  | 14   | 0.7986          | -0.0083   |
+| 0.802         | 2.93  | 21   | 0.6902          | 0.2336    |
+| 0.7469        | 3.93  | 28   | 0.6665          | 0.3001    |
+| 0.7519        | 4.93  | 35   | 0.6578          | 0.3895    |
+| 0.7247        | 5.93  | 42   | 0.6346          | 0.3682    |
+| 0.6991        | 6.93  | 49   | 0.8796          | 0.3681    |
+| 0.6829        | 7.93  | 56   | 0.6098          | 0.3747    |
+| 0.7241        | 8.93  | 63   | 0.7538          | 0.4345    |
+| 0.6703        | 9.93  | 70   | 0.5646          | 0.4419    |
+| 0.6415        | 10.93 | 77   | 1.6112          | 0.3947    |
+| 1.0551        | 11.93 | 84   | 1.9104          | 0.4256    |
+| 1.2621        | 12.93 | 91   | 0.5694          | 0.4640    |
+| 0.7165        | 13.93 | 98   | 0.5647          | 0.4748    |
+| 0.602         | 14.93 | 105  | 0.3979          | 0.4907    |
+| 0.4668        | 15.93 | 112  | 0.3896          | 0.4891    |
+| 0.5248        | 16.93 | 119  | 0.5101          | 0.4878    |
+| 0.6232        | 17.93 | 126  | 0.3298          | 0.5128    |
+| 0.5491        | 18.93 | 133  | 0.6220          | 0.5210    |
+| 0.5022        | 19.93 | 140  | 0.5351          | 0.5212    |
+| 0.7122        | 20.93 | 147  | 0.3773          | 0.5278    |
+| 0.377         | 21.93 | 154  | 0.3368          | 0.5278    |
+| 0.3689        | 22.93 | 161  | 0.4503          | 0.5266    |
+| 0.3768        | 23.93 | 168  | 0.3237          | 0.5428    |
+| 0.3308        | 24.93 | 175  | 0.2850          | 0.5559    |
+| 0.3182        | 25.93 | 182  | 0.2804          | 0.5611    |
+| 0.3135        | 26.93 | 189  | 0.2792          | 0.5660    |
+| 0.2953        | 27.93 | 196  | 0.2669          | 0.5707    |
+| 0.2917        | 28.93 | 203  | 0.2654          | 0.5742    |
+| 0.2652        | 29.93 | 210  | 0.2709          | 0.5742    |
 
 
 ### Framework versions