End of training

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: transformers
 license: mit
-base_model: microsoft/deberta-base
+base_model: microsoft/deberta-v3-base
 tags:
 - generated_from_trainer
 metrics:
@@ -16,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # deberta_textclassification
 
-This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3436
-- Accuracy: 0.9520
+- Loss: 0.3802
+- Accuracy: 0.9487
 
 ## Model description
 
@@ -48,25 +48,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.3919        | 0.2924 | 500  | 0.2821          | 0.9184   |
-| 0.274         | 0.5848 | 1000 | 0.2795          | 0.9362   |
-| 0.2552        | 0.8772 | 1500 | 0.2469          | 0.9355   |
-| 0.2148        | 1.1696 | 2000 | 0.3214          | 0.9421   |
-| 0.1876        | 1.4620 | 2500 | 0.2636          | 0.9382   |
-| 0.1505        | 1.7544 | 3000 | 0.2323          | 0.9467   |
-| 0.1411        | 2.0468 | 3500 | 0.3445          | 0.9395   |
-| 0.0676        | 2.3392 | 4000 | 0.3280          | 0.9414   |
-| 0.1089        | 2.6316 | 4500 | 0.4225          | 0.9270   |
-| 0.0888        | 2.9240 | 5000 | 0.2458          | 0.9520   |
-| 0.0544        | 3.2164 | 5500 | 0.2877          | 0.9539   |
-| 0.0366        | 3.5088 | 6000 | 0.3010          | 0.9553   |
-| 0.0322        | 3.8012 | 6500 | 0.3508          | 0.9474   |
-| 0.0313        | 4.0936 | 7000 | 0.3302          | 0.9520   |
-| 0.0191        | 4.3860 | 7500 | 0.3527          | 0.9493   |
-| 0.0118        | 4.6784 | 8000 | 0.3378          | 0.9513   |
-| 0.0189        | 4.9708 | 8500 | 0.3436          | 0.9520   |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2717        | 1.0   | 1330 | 0.2609          | 0.9351   |
+| 0.1697        | 2.0   | 2660 | 0.2156          | 0.9452   |
+| 0.0895        | 3.0   | 3990 | 0.3175          | 0.9465   |
+| 0.0343        | 4.0   | 5320 | 0.3872          | 0.9450   |
+| 0.0165        | 5.0   | 6650 | 0.3802          | 0.9487   |
 
 
 ### Framework versions