End of training

README.md

@@ -1,5 +1,6 @@
 ---
 license: apache-2.0
+base_model: distilbert-base-uncased
 tags:
 - generated_from_trainer
 datasets:
@@ -21,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9025229357798165
+      value: 0.8990825688073395
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +32,8 @@ 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 glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2805
-- Accuracy: 0.9025
+- Loss: 0.3077
+- Accuracy: 0.8991
 
 ## Model description
 
@@ -63,16 +64,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 132  | 0.2592          | 0.8888   |
-| No log        | 2.0   | 264  | 0.2770          | 0.8979   |
-| No log        | 3.0   | 396  | 0.2805          | 0.9025   |
-| 0.1914        | 4.0   | 528  | 0.2975          | 0.9014   |
-| 0.1914        | 5.0   | 660  | 0.3026          | 0.9002   |
+| No log        | 1.0   | 132  | 0.2548          | 0.8888   |
+| No log        | 2.0   | 264  | 0.2657          | 0.8956   |
+| No log        | 3.0   | 396  | 0.2755          | 0.8968   |
+| 0.1961        | 4.0   | 528  | 0.2946          | 0.8956   |
+| 0.1961        | 5.0   | 660  | 0.3077          | 0.8991   |
 
 
 ### Framework versions
 
-- Transformers 4.29.1
-- Pytorch 2.0.1+cu117
-- Datasets 2.12.0
-- Tokenizers 0.13.3
+- Transformers 4.35.2
+- Pytorch 2.1.1+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0