End of training

README.md

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+---
+library_name: transformers
+base_model: microsoft/graphcodebert-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: vuln-patch-cwe-guesser-model-microsoft-graphcodebert-base
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# vuln-patch-cwe-guesser-model-microsoft-graphcodebert-base
+
+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
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- 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
+- 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 |
+
+
+### Framework versions
+
+- Transformers 4.55.0
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.2

emissions.csv

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+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

metrics.json

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+{
+    "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
+}