End of training

README.md

@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/graphcodebert-base](https://huggingface.co/microsoft/graphcodebert-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 4.8358
-- Accuracy: 0.25
-- F1: 0.0679
+- Loss: 4.8276
+- Accuracy: 0.35
+- F1: 0.1264
 
 ## Model description
 
@@ -52,11 +52,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 1    | 5.1228          | 0.15     | 0.0789 |
-| No log        | 2.0   | 2    | 5.0219          | 0.15     | 0.0160 |
-| No log        | 3.0   | 3    | 4.9351          | 0.15     | 0.0163 |
-| No log        | 4.0   | 4    | 4.8705          | 0.25     | 0.0679 |
-| No log        | 5.0   | 5    | 4.8358          | 0.25     | 0.0679 |
+| No log        | 1.0   | 1    | 5.1591          | 0.0      | 0.0    |
+| No log        | 2.0   | 2    | 5.0441          | 0.3      | 0.0985 |
+| No log        | 3.0   | 3    | 4.9430          | 0.45     | 0.1833 |
+| No log        | 4.0   | 4    | 4.8677          | 0.35     | 0.1264 |
+| No log        | 5.0   | 5    | 4.8276          | 0.35     | 0.1264 |
 
 
 ### Framework versions

metrics.json

@@ -1,9 +1,9 @@
 {
-    "eval_loss": 4.835766792297363,
-    "eval_accuracy": 0.25,
-    "eval_f1": 0.06785714285714287,
-    "eval_runtime": 0.103,
-    "eval_samples_per_second": 194.189,
-    "eval_steps_per_second": 9.709,
+    "eval_loss": 4.827600955963135,
+    "eval_accuracy": 0.35,
+    "eval_f1": 0.12637362637362637,
+    "eval_runtime": 0.1882,
+    "eval_samples_per_second": 106.249,
+    "eval_steps_per_second": 5.312,
     "epoch": 5.0
 }

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:06e58256b692deead662a275d118052a8e014fbb92fe42dcea9dda39fc1c1c34
 size 499178808