End of training

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9108920951026214
+      value: 0.9082503556187767
 ---
 
 <!-- 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 [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the snli dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2573
-- Accuracy: 0.9109
+- Loss: 0.2611
+- Accuracy: 0.9083
 
 ## Model description
 
@@ -52,7 +52,7 @@ The following hyperparameters were used during training:
 - learning_rate: 2e-05
 - train_batch_size: 256
 - eval_batch_size: 128
-- seed: 81
+- seed: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 3
@@ -61,9 +61,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.367         | 1.0   | 2146 | 0.2850          | 0.8987   |
-| 0.3208        | 2.0   | 4292 | 0.2633          | 0.9064   |
-| 0.2926        | 3.0   | 6438 | 0.2573          | 0.9109   |
+| 0.3697        | 1.0   | 2146 | 0.2888          | 0.8993   |
+| 0.3223        | 2.0   | 4292 | 0.2650          | 0.9075   |
+| 0.2916        | 3.0   | 6438 | 0.2611          | 0.9083   |
 
 
 ### Framework versions