Training completed!

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9193548387096774
+      value: 0.9174193548387096
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +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 clinc_oos dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7772
-- Accuracy: 0.9194
+- Loss: 0.8027
+- Accuracy: 0.9174
 
 ## Model description
 
@@ -64,16 +64,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 318  | 3.2994          | 0.7287   |
-| 3.7943        | 2.0   | 636  | 1.8855          | 0.8381   |
-| 3.7943        | 3.0   | 954  | 1.1624          | 0.8990   |
-| 1.6954        | 4.0   | 1272 | 0.8625          | 0.9119   |
-| 0.8982        | 5.0   | 1590 | 0.7772          | 0.9194   |
+| No log        | 1.0   | 318  | 3.3202          | 0.7174   |
+| 3.8199        | 2.0   | 636  | 1.9119          | 0.8542   |
+| 3.8199        | 3.0   | 954  | 1.1932          | 0.8952   |
+| 1.7381        | 4.0   | 1272 | 0.8882          | 0.9110   |
+| 0.932         | 5.0   | 1590 | 0.8027          | 0.9174   |
 
 
 ### Framework versions
 
-- Transformers 4.35.2
+- Transformers 4.36.2
 - Pytorch 2.1.1+cu118
-- Datasets 2.15.0
+- Datasets 2.16.1
 - Tokenizers 0.15.0

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:79621d85d469fbd0ccaadc92fe2506f0de3ab61822336d0fb940202c4aa66f46
 size 268290900