update model card README.md

README.md

@@ -1,5 +1,4 @@
 ---
-license: apache-2.0
 tags:
 - generated_from_trainer
 metrics:
@@ -14,13 +13,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # t5-v1_1-base-squadV2AutoQgen
 
-This model is a fine-tuned version of [google/t5-v1_1-base](https://huggingface.co/google/t5-v1_1-base) on an unknown dataset.
+This model was trained from scratch on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5863
-- Rouge1: 0.1449
-- Rouge2: 0.0701
-- Rougel: 0.1268
-- Rougelsum: 0.1397
+- Loss: 1.6476
+- Rouge1: 0.1407
+- Rouge2: 0.0716
+- Rougel: 0.1245
+- Rougelsum: 0.1356
 
 ## Model description
 
@@ -39,22 +38,24 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 0.0003
 - train_batch_size: 4
 - eval_batch_size: 4
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 4
+- num_epochs: 6
 
 ### Training results
 
 | Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
 |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
-| 2.0146        | 1.0   | 4758  | 1.6980          | 0.143  | 0.0705 | 0.1257 | 0.1384    |
-| 1.8197        | 2.0   | 9516  | 1.6290          | 0.1479 | 0.0716 | 0.1293 | 0.143     |
-| 1.7023        | 3.0   | 14274 | 1.5961          | 0.1453 | 0.0711 | 0.1276 | 0.1402    |
-| 1.6314        | 4.0   | 19032 | 1.5863          | 0.1449 | 0.0701 | 0.1268 | 0.1397    |
+| 1.628         | 1.0   | 4758  | 1.6606          | 0.1404 | 0.0711 | 0.1242 | 0.136     |
+| 1.4999        | 2.0   | 9516  | 1.6372          | 0.1443 | 0.0727 | 0.1272 | 0.1389    |
+| 1.3838        | 3.0   | 14274 | 1.6311          | 0.1427 | 0.0719 | 0.1254 | 0.1375    |
+| 1.2908        | 4.0   | 19032 | 1.6260          | 0.1383 | 0.0705 | 0.1231 | 0.1335    |
+| 1.1733        | 5.0   | 23790 | 1.6319          | 0.1404 | 0.0718 | 0.1239 | 0.1351    |
+| 1.1225        | 6.0   | 28548 | 1.6476          | 0.1407 | 0.0716 | 0.1245 | 0.1356    |
 
 
 ### Framework versions