End of training

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9129242023978866
+      value: 0.9141434667750458
 ---
 
 <!-- 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 [openai-community/gpt2-large](https://huggingface.co/openai-community/gpt2-large) on the snli dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2951
-- Accuracy: 0.9129
+- Loss: 0.2938
+- Accuracy: 0.9141
 
 ## Model description
 
@@ -52,7 +52,7 @@ The following hyperparameters were used during training:
 - learning_rate: 2e-05
 - train_batch_size: 128
 - eval_batch_size: 128
-- seed: 11
+- seed: 79
 - 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 |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 0.3126        | 1.0   | 4292  | 0.2558          | 0.9093   |
-| 0.2258        | 2.0   | 8584  | 0.2555          | 0.9133   |
-| 0.1471        | 3.0   | 12876 | 0.2951          | 0.9129   |
+| 0.3107        | 1.0   | 4292  | 0.2590          | 0.9091   |
+| 0.2181        | 2.0   | 8584  | 0.2598          | 0.9131   |
+| 0.1441        | 3.0   | 12876 | 0.2938          | 0.9141   |
 
 
 ### Framework versions