update model card README.md

README.md

@@ -13,7 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [VuongQuoc/my_awesome_swag_model](https://huggingface.co/VuongQuoc/my_awesome_swag_model) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5594
+- Loss: 1.6094
 
 ## Model description
 
@@ -32,26 +32,34 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-06
+- learning_rate: 3e-05
 - train_batch_size: 2
 - eval_batch_size: 4
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.8
-- num_epochs: 1
+- lr_scheduler_warmup_ratio: 0.6
+- num_epochs: 2
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 0.7547        | 0.13  | 700  | 1.2948          |
-| 0.5101        | 0.26  | 1400 | 1.4142          |
-| 0.3566        | 0.38  | 2100 | 1.5164          |
-| 0.2476        | 0.51  | 2800 | 1.5077          |
-| 0.156         | 0.64  | 3500 | 1.4539          |
-| 0.1178        | 0.77  | 4200 | 1.6601          |
-| 0.1148        | 0.89  | 4900 | 1.5594          |
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 0.8462        | 0.13  | 700   | 1.7281          |
+| 0.4775        | 0.26  | 1400  | 1.6819          |
+| 0.3949        | 0.38  | 2100  | 1.8476          |
+| 0.3923        | 0.51  | 2800  | 2.2831          |
+| 1.1178        | 0.64  | 3500  | 1.6094          |
+| 1.6198        | 0.77  | 4200  | 1.6094          |
+| 1.6156        | 0.89  | 4900  | 1.6094          |
+| 1.6151        | 1.02  | 5600  | 1.6094          |
+| 1.615         | 1.15  | 6300  | 1.6094          |
+| 1.6113        | 1.28  | 7000  | 1.6094          |
+| 1.6133        | 1.41  | 7700  | 1.6094          |
+| 1.6114        | 1.53  | 8400  | 1.6094          |
+| 1.6108        | 1.66  | 9100  | 1.6094          |
+| 1.6155        | 1.79  | 9800  | 1.6094          |
+| 1.6087        | 1.92  | 10500 | 1.6094          |
 
 
 ### Framework versions