Text Generation
PEFT
TensorBoard
Safetensors
code
differential-privacy
code-generation
continued-pretraining
lora
dp-sgd
opacus
privacy
Instructions to use melihcatal/codedp-cpt-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use melihcatal/codedp-cpt-models with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
| { | |
| "audit/delta": 1e-05, | |
| "audit/embedding/auc": 0.916224, | |
| "audit/embedding/empirical_epsilon/0.01": 3.023197554051876, | |
| "audit/embedding/empirical_epsilon/0.05": 3.4791953936219215, | |
| "audit/embedding/empirical_epsilon_details/0.01/correct_guesses": 100.0, | |
| "audit/embedding/empirical_epsilon_details/0.01/epsilon": 3.023197554051876, | |
| "audit/embedding/empirical_epsilon_details/0.01/num_guesses": 100.0, | |
| "audit/embedding/empirical_epsilon_details/0.05/correct_guesses": 100.0, | |
| "audit/embedding/empirical_epsilon_details/0.05/epsilon": 3.4791953936219215, | |
| "audit/embedding/empirical_epsilon_details/0.05/num_guesses": 100.0, | |
| "audit/loss/auc": 1.0, | |
| "audit/loss/empirical_epsilon/0.01": 3.023197554051876, | |
| "audit/loss/empirical_epsilon/0.05": 3.4791953936219215, | |
| "audit/loss/empirical_epsilon_details/0.01/correct_guesses": 100.0, | |
| "audit/loss/empirical_epsilon_details/0.01/epsilon": 3.023197554051876, | |
| "audit/loss/empirical_epsilon_details/0.01/num_guesses": 100.0, | |
| "audit/loss/empirical_epsilon_details/0.05/correct_guesses": 100.0, | |
| "audit/loss/empirical_epsilon_details/0.05/epsilon": 3.4791953936219215, | |
| "audit/loss/empirical_epsilon_details/0.05/num_guesses": 100.0, | |
| "audit/num_canaries": 500.0, | |
| "audit/num_members": 250.0, | |
| "audit/paper_guess_fraction": 0.2, | |
| "audit/paper_guess_steps": 20.0, | |
| "energy/codecarbon/cpu_count": 224.0, | |
| "energy/codecarbon/cpu_energy": 0.18368298514637418, | |
| "energy/codecarbon/cpu_power": 179.3439937196561, | |
| "energy/codecarbon/cpu_utilization_percent": 2.2497114375655825, | |
| "energy/codecarbon/duration": 3820.65162669681, | |
| "energy/codecarbon/emissions": 0.5568149811716148, | |
| "energy/codecarbon/emissions_rate": 0.0001457382236267942, | |
| "energy/codecarbon/energy_consumed": 2.7126092523666183, | |
| "energy/codecarbon/gpu_count": 4.0, | |
| "energy/codecarbon/gpu_energy": 2.457235179675422, | |
| "energy/codecarbon/gpu_power": 2316.658494927477, | |
| "energy/codecarbon/gpu_utilization_percent": 96.45330535152151, | |
| "energy/codecarbon/latitude": 37.3541, | |
| "energy/codecarbon/longitude": -121.9552, | |
| "energy/codecarbon/pue": 1.0, | |
| "energy/codecarbon/ram_energy": 0.07169108754482326, | |
| "energy/codecarbon/ram_power": 70.0, | |
| "energy/codecarbon/ram_total_size": 2015.5625190734863, | |
| "energy/codecarbon/ram_used_gb": 46.78091819539025, | |
| "energy/codecarbon/ram_utilization_percent": 2.3057974816369358, | |
| "energy/codecarbon/water_consumed": 0.0, | |
| "energy/codecarbon/wue": 0.0, | |
| "eval/duration_sec": 27.13153049722314, | |
| "eval/loss": 0.7454980848164394, | |
| "perf/audit_duration_sec": 6.722778998315334, | |
| "perf/epoch_duration_sec": 1814.1021996028721, | |
| "perf/epoch_samples": 53997.0, | |
| "perf/epoch_samples_per_sec": 29.765136722628178, | |
| "perf/epoch_tokens": 43876231.0, | |
| "perf/epoch_tokens_per_sec": 24186.19579955584, | |
| "perf/gradient_accumulation_steps": 8.0, | |
| "perf/logical_batch_size": 66.0, | |
| "perf/logical_token_count": 55694.0, | |
| "perf/samples_per_sec": 7.877740262760654, | |
| "perf/step_duration_sec": 8.378037076443434, | |
| "perf/tokens_per_sec": 6647.619184760483, | |
| "system/cuda_epoch_peak_memory_gb": 88.38552379608154, | |
| "system/cuda_max_memory_allocated_gb": 88.38552379608154, | |
| "system/cuda_memory_allocated_gb": 17.816345691680908, | |
| "train/epoch_canary_loss": 1.0832555509625612, | |
| "train/epoch_loss": 0.840315752633972, | |
| "train/epoch_real_loss": 0.8362452851041504, | |
| "train/lr": 2.5558633627303928e-08, | |
| "train/step_canary_loss": 0.94140625, | |
| "train/step_loss": 0.854436350591255, | |
| "train/step_real_loss": 0.8517185375094414 | |
| } |