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/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 3.4697
-- Accuracy: 0.4535
-- F1: 0.0330
+- Loss: 4.0524
+- Accuracy: 0.3448
+- F1: 0.0285
 
 ## Model description
 
@@ -52,11 +52,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 4.6623        | 1.0   | 20   | 4.0312          | 0.3023   | 0.0122 |
-| 4.1733        | 2.0   | 40   | 3.9241          | 0.3721   | 0.0265 |
-| 4.0474        | 3.0   | 60   | 3.8249          | 0.4419   | 0.0324 |
-| 3.8755        | 4.0   | 80   | 3.5504          | 0.4651   | 0.0357 |
-| 3.6768        | 5.0   | 100  | 3.4697          | 0.4535   | 0.0330 |
+| 4.6485        | 1.0   | 20   | 4.3362          | 0.2184   | 0.0081 |
+| 4.1158        | 2.0   | 40   | 4.2805          | 0.2184   | 0.0081 |
+| 4.0339        | 3.0   | 60   | 4.2431          | 0.2299   | 0.0132 |
+| 3.928         | 4.0   | 80   | 4.1519          | 0.3103   | 0.0257 |
+| 3.7985        | 5.0   | 100  | 4.0524          | 0.3448   | 0.0285 |
 
 
 ### 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
-2025-08-11T10:14:28,codecarbon,d2500f10-db48-48f0-93da-6c6855365939,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,61.5074503980577,0.001099743166948356,1.787983666744678e-05,42.5,383.1514374431581,94.34468364715576,0.0007257662079355215,0.008110773433116947,0.0016110361163205477,0.010447575757373017,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
+2025-08-11T12:39:05,codecarbon,fdf156c8-5087-44f0-a6bf-de132f3f71d4,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,58.661103307269514,0.001053369369711213,1.7956862560078636e-05,42.5,462.4422479400818,94.34468364715576,0.0006920252260519192,0.0077788331675208156,0.0015361656292198214,0.010007024022792556,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": 3.4697318077087402,
-    "eval_accuracy": 0.45348837209302323,
-    "eval_f1": 0.03298874813820767,
-    "eval_runtime": 0.294,
-    "eval_samples_per_second": 292.517,
-    "eval_steps_per_second": 10.204,
+    "eval_loss": 4.052394390106201,
+    "eval_accuracy": 0.3448275862068966,
+    "eval_f1": 0.028517181742988194,
+    "eval_runtime": 0.5138,
+    "eval_samples_per_second": 169.342,
+    "eval_steps_per_second": 5.839,
     "epoch": 5.0
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4a7db349bebda9365ca308a7f9059c7f1949679fcc0aca6d1292e9f22c5742b5
+oid sha256:4210bd3289a129cc2cf3cd06e66d3ea4ab467e68e33c6f1fa4887e308e75c90b
 size 499178808