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: 4.0621
-- Accuracy: 0.3372
-- F1: 0.0123
+- Loss: 3.2520
+- Accuracy: 0.4831
+- F1: 0.0406
 
 ## Model description
 
@@ -40,19 +40,23 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 3e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 40
+- eval_batch_size: 40
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 5
 - label_smoothing_factor: 0.1
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 4.6512        | 1.0   | 25   | 4.0621          | 0.3372   | 0.0123 |
+| 4.6203        | 1.0   | 20   | 3.9289          | 0.3258   | 0.0126 |
+| 4.1133        | 2.0   | 40   | 3.7132          | 0.4494   | 0.0365 |
+| 3.8534        | 3.0   | 60   | 3.3958          | 0.4831   | 0.0392 |
+| 3.5811        | 4.0   | 80   | 3.2843          | 0.4831   | 0.0396 |
+| 3.4742        | 5.0   | 100  | 3.2520          | 0.4831   | 0.0406 |
 
 
 ### Framework versions

emissions.csv

@@ -1,2 +1,2 @@
 timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-08-11T09:43:01,codecarbon,113d738a-e210-4483-bb6a-9ee16e791338,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,12.953200169838965,0.00022455010525202892,1.73354925661448e-05,42.5,456.2447039091083,94.34468364715576,0.0001528648026164673,0.001641035201799923,0.0003393291953216839,0.002133229199738074,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-60-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58582305908203,machine,N,1.0
+2025-08-11T10:17:09,codecarbon,215d81bb-4dc1-4c7a-b3cb-016ca4e55fa8,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,58.27186329010874,0.001046931100390279,1.796632270325889e-05,42.5,465.8439992179711,94.34468364715576,0.0006876452240944168,0.0077317739631723725,0.0015264411852314193,0.009945860372498208,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-60-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58582305908203,machine,N,1.0

metrics.json

@@ -1,9 +1,9 @@
 {
-    "eval_loss": 4.062078952789307,
-    "eval_accuracy": 0.3372093023255814,
-    "eval_f1": 0.012301166489925769,
-    "eval_runtime": 0.382,
-    "eval_samples_per_second": 225.148,
-    "eval_steps_per_second": 7.854,
-    "epoch": 1.0
+    "eval_loss": 3.2520461082458496,
+    "eval_accuracy": 0.48314606741573035,
+    "eval_f1": 0.040641505810045137,
+    "eval_runtime": 0.4561,
+    "eval_samples_per_second": 195.136,
+    "eval_steps_per_second": 6.578,
+    "epoch": 5.0
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:44ab007c4ab9a9484c6213f3f3b24853e0bace7907792bd0b8e2ecacca00c6b2
+oid sha256:c92434b8384240932fe7db74d57db37087fcacbbf0176b3542ef2697361b1fe1
 size 499178808