Update README.md

README.md

@@ -7,7 +7,7 @@ tags:
 - full
 - generated_from_trainer
 metrics:
-- accuracy
+- val accuracy
 model-index:
 - name: reward
   results: []
@@ -18,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # reward
 
-This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the gsm8k_llama3.2-1B_128_1ep dataset.
+This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the gsm8k_llama3.1-8B_128_1ep dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.2467
-- Accuracy: 0.8810
+- val Accuracy: 0.8810
 
 ## Model description
 
@@ -56,19 +56,19 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.609         | 0.0856 | 5    | 0.4890          | 0.8135   |
-| 0.3044        | 0.1711 | 10   | 0.2622          | 0.9204   |
-| 0.3091        | 0.2567 | 15   | 0.1574          | 0.9060   |
-| 0.2377        | 0.3422 | 20   | 0.2161          | 0.9090   |
-| 0.2227        | 0.4278 | 25   | 0.2810          | 0.8696   |
-| 0.3034        | 0.5134 | 30   | 0.2796          | 0.8832   |
-| 0.2101        | 0.5989 | 35   | 0.2074          | 0.9022   |
-| 0.2027        | 0.6845 | 40   | 0.1866          | 0.9075   |
-| 0.2683        | 0.7701 | 45   | 0.2167          | 0.8976   |
-| 0.1873        | 0.8556 | 50   | 0.2340          | 0.8878   |
-| 0.2984        | 0.9412 | 55   | 0.2451          | 0.8825   |
+| Training Loss | Epoch  | Step | Validation Loss | val Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:------------:|
+| 0.609         | 0.0856 | 5    | 0.4890          | 0.8135       |
+| 0.3044        | 0.1711 | 10   | 0.2622          | 0.9204       |
+| 0.3091        | 0.2567 | 15   | 0.1574          | 0.9060       |
+| 0.2377        | 0.3422 | 20   | 0.2161          | 0.9090       |
+| 0.2227        | 0.4278 | 25   | 0.2810          | 0.8696       |
+| 0.3034        | 0.5134 | 30   | 0.2796          | 0.8832       |
+| 0.2101        | 0.5989 | 35   | 0.2074          | 0.9022       |
+| 0.2027        | 0.6845 | 40   | 0.1866          | 0.9075       |
+| 0.2683        | 0.7701 | 45   | 0.2167          | 0.8976       |
+| 0.1873        | 0.8556 | 50   | 0.2340          | 0.8878       |
+| 0.2984        | 0.9412 | 55   | 0.2451          | 0.8825       |
 
 
 ### Framework versions