Text Generation
PyTorch
English
jl_code_python
code
python
python-code
code-generation
code-completion
causal-language-modeling
decoder-only
programming-language-model
small-language-model
from-scratch
random-initialization
custom-architecture
custom-pytorch
byte-level-bpe
rope
rmsnorm
swiglu
consumer-gpu
rtx-3060
research
jumplander
jl-code
| { | |
| "run_name": "JL-Code-Python-97M-v0.1-base", | |
| "status": "completed", | |
| "model_repository": "jumplander/JL-Code-Python-97M", | |
| "objective": "causal-language-modeling", | |
| "training_from_scratch": true, | |
| "base_model": null, | |
| "model_parameters": 97536768, | |
| "total_optimizer_steps": 10000, | |
| "micro_batch_size": 1, | |
| "gradient_accumulation_steps": 32, | |
| "effective_batch_size_sequences": 32, | |
| "sequence_length": 1024, | |
| "tokens_per_optimizer_step": 32768, | |
| "estimated_tokens_processed": 327680000, | |
| "optimizer": { | |
| "name": "AdamW", | |
| "learning_rate": 0.0003, | |
| "minimum_learning_rate": 3e-05, | |
| "betas": [ | |
| 0.9, | |
| 0.95 | |
| ], | |
| "epsilon": 1e-08, | |
| "weight_decay": 0.1, | |
| "fused_when_available": true | |
| }, | |
| "scheduler": { | |
| "name": "cosine-decay", | |
| "warmup_steps": 200 | |
| }, | |
| "gradient_clipping": { | |
| "enabled": true, | |
| "max_norm": 1.0 | |
| }, | |
| "precision": { | |
| "device": "cuda", | |
| "dtype": "bfloat16", | |
| "automatic_mixed_precision": true, | |
| "gradient_scaler_used_for_fp16_only": true | |
| }, | |
| "checkpointing": { | |
| "save_interval_steps": 500, | |
| "format_version": 1, | |
| "includes_optimizer_state": true, | |
| "checkpoint_file": "jumplander_python_100m.pt" | |
| }, | |
| "evaluation": { | |
| "validation_interval_steps": 250, | |
| "validation_batches": 20, | |
| "benchmark_results_published": false | |
| }, | |
| "logging": { | |
| "log_interval_steps": 10 | |
| }, | |
| "random_seed": 1337, | |
| "num_workers": 0, | |
| "hardware": { | |
| "gpu": "NVIDIA GeForce RTX 3060", | |
| "gpu_memory_gb": 12, | |
| "observed_peak_allocated_vram_gb_approx": 1.86, | |
| "observed_tokens_per_second_range_approx": [ | |
| 8400, | |
| 9000 | |
| ] | |
| }, | |
| "tokenizer": { | |
| "type": "Byte-Level BPE", | |
| "target_vocab_size": 16384, | |
| "minimum_frequency": 2, | |
| "byte_fallback": true | |
| }, | |
| "data": { | |
| "sources": [ | |
| { | |
| "id": "codeparrot/codeparrot-clean", | |
| "role": "python-source-pretraining" | |
| }, | |
| { | |
| "id": "google-research-datasets/mbpp", | |
| "role": "english-to-python-and-held-out-tasks" | |
| } | |
| ], | |
| "accepted_base_samples": 20000, | |
| "train_rows": 35855, | |
| "validation_rows": 389, | |
| "test_rows": 793, | |
| "source_records_read": 10809, | |
| "rejected_exact_duplicates": 391, | |
| "rejected_generated_files": 246, | |
| "rejected_secret_like_samples": 75, | |
| "rejected_syntax_invalid_samples": 1523, | |
| "rejected_oversized_samples": 268, | |
| "fill_in_the_middle_variants": true, | |
| "python_ast_validation": true, | |
| "sha256_exact_deduplication": true | |
| } | |
| } | |