End of training

README.md

@@ -19,7 +19,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9195
+      value: 0.9155
 ---
 
 <!-- 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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2489
-- Accuracy: 0.9195
+- Loss: 0.2515
+- Accuracy: 0.9155
 
 ## Model description
 
@@ -63,7 +63,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.9165        | 1.0   | 500  | 0.2489          | 0.9195   |
+| 0.9465        | 1.0   | 500  | 0.2515          | 0.9155   |
 
 
 ### Framework versions

eval_results.txt

@@ -1,6 +1,6 @@
 epoch = 1.0
-eval_accuracy = 0.9195
-eval_loss = 0.24885223805904388
-eval_runtime = 5.1888
-eval_samples_per_second = 385.447
-eval_steps_per_second = 6.167
+eval_accuracy = 0.9155
+eval_loss = 0.2514632046222687
+eval_runtime = 4.962
+eval_samples_per_second = 403.061
+eval_steps_per_second = 6.449