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End of training

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  1. README.md +8 -8
  2. emissions.csv +1 -1
  3. metrics.json +6 -6
  4. model.safetensors +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 4.0524
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- - Accuracy: 0.3448
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- - F1: 0.0285
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  ## Model description
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@@ -52,11 +52,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 4.6485 | 1.0 | 20 | 4.3362 | 0.2184 | 0.0081 |
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- | 4.1158 | 2.0 | 40 | 4.2805 | 0.2184 | 0.0081 |
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- | 4.0339 | 3.0 | 60 | 4.2431 | 0.2299 | 0.0132 |
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- | 3.928 | 4.0 | 80 | 4.1519 | 0.3103 | 0.0257 |
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- | 3.7985 | 5.0 | 100 | 4.0524 | 0.3448 | 0.0285 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 4.8689
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+ - Accuracy: 0.35
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+ - F1: 0.0519
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 1 | 5.1648 | 0.0 | 0.0 |
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+ | No log | 2.0 | 2 | 5.0523 | 0.05 | 0.0167 |
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+ | No log | 3.0 | 3 | 4.9636 | 0.35 | 0.0519 |
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+ | No log | 4.0 | 4 | 4.9016 | 0.35 | 0.0519 |
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+ | No log | 5.0 | 5 | 4.8689 | 0.35 | 0.0519 |
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  ### Framework versions
emissions.csv CHANGED
@@ -1,2 +1,2 @@
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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
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- 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
 
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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
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+ 2025-08-11T13:36:59,codecarbon,25e13009-9525-47a3-9dc4-79f6b0744b00,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,12.463868889026344,0.0001911372220953498,1.5335304294129263e-05,42.5,387.9151934865297,94.34468364715576,0.00014706192220393052,0.0013422999627152876,0.0003264444486961051,0.0018158063336153234,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 CHANGED
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  {
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- "eval_loss": 4.052394390106201,
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- "eval_accuracy": 0.3448275862068966,
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- "eval_f1": 0.028517181742988194,
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- "eval_runtime": 0.5138,
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- "eval_samples_per_second": 169.342,
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- "eval_steps_per_second": 5.839,
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  "epoch": 5.0
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  }
 
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  {
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+ "eval_loss": 4.868948936462402,
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+ "eval_accuracy": 0.35,
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+ "eval_f1": 0.05185185185185185,
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+ "eval_runtime": 0.1086,
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+ "eval_samples_per_second": 184.157,
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+ "eval_steps_per_second": 9.208,
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  "epoch": 5.0
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  }
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