update model card README.md

README.md

@@ -2,6 +2,9 @@
 license: bsd-3-clause
 tags:
 - generated_from_trainer
+metrics:
+- rouge
+- bleu
 model-index:
 - name: CommitPredictorT5
   results: []
@@ -13,6 +16,14 @@ should probably proofread and complete it, then remove this comment. -->
 # CommitPredictorT5
 
 This model is a fine-tuned version of [Salesforce/codet5-base-multi-sum](https://huggingface.co/Salesforce/codet5-base-multi-sum) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.7376
+- Rouge1: 0.3735
+- Rouge2: 0.1504
+- Rougel: 0.3701
+- Rougelsum: 0.3697
+- Gen Len: 19.1365
+- Bleu: 0.1453
 
 ## Model description
 
@@ -32,15 +43,37 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 100
 
 ### Training results
 
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu   |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|
+| 3.2138        | 1.0   | 687   | 2.6919          | 0.3246 | 0.0964 | 0.3216 | 0.3218    | 9.125   | 0.0937 |
+| 2.7517        | 2.0   | 1374  | 2.5546          | 0.3394 | 0.1042 | 0.3364 | 0.3362    | 8.9803  | 0.1066 |
+| 2.4305        | 3.0   | 2061  | 2.4836          | 0.3523 | 0.1136 | 0.3496 | 0.3496    | 9.2049  | 0.1123 |
+| 2.2956        | 4.0   | 2748  | 2.4483          | 0.3658 | 0.126  | 0.3633 | 0.3633    | 9.525   | 0.1146 |
+| 2.1888        | 5.0   | 3435  | 2.4312          | 0.3665 | 0.1332 | 0.3636 | 0.3634    | 10.0631 | 0.1253 |
+| 2.0056        | 6.0   | 4122  | 2.4251          | 0.3674 | 0.1352 | 0.3646 | 0.3644    | 9.8365  | 0.1240 |
+| 1.9128        | 7.0   | 4809  | 2.4289          | 0.3725 | 0.1431 | 0.3694 | 0.3694    | 9.8713  | 0.1295 |
+| 1.8487        | 8.0   | 5496  | 2.4625          | 0.3683 | 0.1377 | 0.3657 | 0.3659    | 10.0947 | 0.1291 |
+| 1.6726        | 9.0   | 6183  | 2.4643          | 0.3725 | 0.1449 | 0.3702 | 0.3697    | 13.1967 | 0.1325 |
+| 1.6292        | 10.0  | 6870  | 2.4716          | 0.3688 | 0.1438 | 0.3664 | 0.3661    | 13.7656 | 0.1307 |
+| 1.5025        | 11.0  | 7557  | 2.4974          | 0.3762 | 0.1494 | 0.3732 | 0.3732    | 14.0988 | 0.1391 |
+| 1.4224        | 12.0  | 8244  | 2.5273          | 0.3723 | 0.1489 | 0.3692 | 0.3688    | 12.084  | 0.1388 |
+| 1.3912        | 13.0  | 8931  | 2.5460          | 0.375  | 0.1499 | 0.3722 | 0.3723    | 13.9529 | 0.1399 |
+| 1.2766        | 14.0  | 9618  | 2.5771          | 0.3698 | 0.1453 | 0.3668 | 0.3667    | 12.5102 | 0.1386 |
+| 1.2188        | 15.0  | 10305 | 2.6005          | 0.3789 | 0.1493 | 0.3763 | 0.376     | 16.0545 | 0.1423 |
+| 1.1779        | 16.0  | 10992 | 2.6296          | 0.3757 | 0.1497 | 0.3729 | 0.3723    | 14.7201 | 0.1423 |
+| 1.0739        | 17.0  | 11679 | 2.6512          | 0.3749 | 0.1522 | 0.3717 | 0.3715    | 16.0008 | 0.1468 |
+| 1.0408        | 18.0  | 12366 | 2.6792          | 0.3758 | 0.1494 | 0.3735 | 0.3733    | 18.4971 | 0.1465 |
+| 0.9567        | 19.0  | 13053 | 2.7153          | 0.3695 | 0.144  | 0.3669 | 0.3667    | 16.2357 | 0.1435 |
+| 0.9072        | 20.0  | 13740 | 2.7376          | 0.3735 | 0.1504 | 0.3701 | 0.3697    | 19.1365 | 0.1453 |
 
 
 ### Framework versions