From 5271774f76021d246a1b920baa2dfa12f96c2ffa Mon Sep 17 00:00:00 2001 From: cuolm Date: Fri, 1 May 2026 16:48:10 +0200 Subject: [PATCH 1/9] fix: filter out tokenized examples exceeding max sequence length - Two-step filtering approach: 1: First pass uses estimated byte_per_token_ratio with max_token_sequence_length to calculate max_bytes_per_subblock = int(config.max_token_sequence_length * bytes_per_token_ratio) and discards code blocks exceeding that estimate. 2. Second pass applies _filter_overlong_tokenized_examples() with actual token counts as hard limit to guarantee no tokenized examples exceed max_token_sequence_length - Eliminates Unsloth max_seq_length overflow risk --- src/codefinetuner/preprocess/config.py | 2 +- src/codefinetuner/preprocess/process.py | 41 ++++++++++++++++++++----- 2 files changed, 35 insertions(+), 8 deletions(-) diff --git a/src/codefinetuner/preprocess/config.py b/src/codefinetuner/preprocess/config.py index acde102..2841bf2 100644 --- a/src/codefinetuner/preprocess/config.py +++ b/src/codefinetuner/preprocess/config.py @@ -24,13 +24,13 @@ class Config: eos_token: str = MISSING data_language: str = MISSING data_extensions: list[str] = MISSING + max_token_sequence_length: int = MISSING # used with bytes_per_token_ratio to convert bytes to tokens, final token count is thus not exact # --- Preprocess Local Parameters --- split_mode: str = "auto" train_ratio: float = 0.8 eval_ratio: float = 0.1 test_ratio: float = 0.1 - max_token_sequence_length: int = 1024 # used with bytes_per_token_ratio to convert bytes to tokens, final token count is thus not exact max_code_blocks_ast_depth: int = 2 # depth 1 is root, 2 includes child nodes (e.g. functions) min_middle_tokens_length: int = 20 # used with estimated bytes_per_token_ratio to convert bytes to tokens, final token count is thus not exact max_middle_tokens_length: int = 200 # used with estimated bytes_per_token_ratio to convert bytes to tokens, final token count is thus not exact diff --git a/src/codefinetuner/preprocess/process.py b/src/codefinetuner/preprocess/process.py index d3b80f9..c98f332 100644 --- a/src/codefinetuner/preprocess/process.py +++ b/src/codefinetuner/preprocess/process.py @@ -63,9 +63,9 @@ def _extract_subblock_ranges(config: Config, node: ts.Node, base_offset: int) -> def _filter_subblocks(subblock_ranges: list[Tuple[int, int]], max_bytes_per_subblock: int) -> list[Tuple[int, int]]: """ - Discard subblocks that have a larger end index than max_bytes_per_subblock + Discard subblocks that have a larger end index than max_bytes_per_subblock. """ - subblock_ranges = sorted(subblock_ranges, key=lambda x: x[1]) # sort ranges by end index + subblock_ranges = sorted(subblock_ranges, key=lambda x: x[1]) # sort ranges by end index i = 0 while i < len(subblock_ranges) and subblock_ranges[i][1] <= max_bytes_per_subblock: i += 1 @@ -126,13 +126,35 @@ def create_fim_examples(config: Config, code_blocks_iter: Iterator[Tuple[bytes, subblock_ranges = _filter_subblocks(subblock_ranges, max_bytes_per_subblock) - code_block_utf8 = code_block_utf8[:max_bytes_per_subblock] # Trunctate code block code if it is larger than bytes_per_code_block, we only consider subblocks inside this range. + code_block_utf8 = code_block_utf8[:max_bytes_per_subblock] # trunctate code block code if it is larger than bytes_per_code_block, we only consider subblocks inside this range. fim_examples = _generate_fim_examples_from_code_block(config, code_block_utf8, subblock_ranges, bytes_per_token_ratio) for fim_example in fim_examples: yield fim_example +def _filter_overlong_tokenized_examples(tokenized_batch: Mapping[str, List[List[int]]], max_length: int) -> Mapping[str, List[List[int]]]: + """ + Remove examples whose actual token count exceeds max_length. + Returns filtered batch. + """ + input_ids = tokenized_batch["input_ids"] + + keep_indices = [] + for idx, token_sequence in enumerate(input_ids): + if len(token_sequence) <= max_length: + keep_indices.append(idx) + + filtered_batch = {} + for key, values in tokenized_batch.items(): + filtered_values = [] + for idx in keep_indices: + filtered_values.append(values[idx]) + filtered_batch[key] = filtered_values + + return filtered_batch + + def _save_tokenized_batch_as_jsonl(file_path: Path, batch: Mapping[str, List[List[int]]]) -> None: with open(file_path, 'a', encoding='utf-8') as f: batch_size = len(batch['input_ids']) @@ -154,7 +176,6 @@ def tokenize_and_save_fim_examples(config: Config, file_path: Path, fim_examples batch = [] for fim_example in fim_examples_iter: batch.append(fim_example.decode('utf-8')) - examples_counter += 1 if (len(batch) == config.tokenizer_batch_size): tokenized_batch = tokenizer( batch, @@ -163,7 +184,10 @@ def tokenize_and_save_fim_examples(config: Config, file_path: Path, fim_examples return_attention_mask=True ) tokenized_batch["labels"] = tokenized_batch["input_ids"] - _save_tokenized_batch_as_jsonl(file_path, tokenized_batch) + filtered_tokenized_batch = _filter_overlong_tokenized_examples(tokenized_batch, config.max_token_sequence_length) + if filtered_tokenized_batch["input_ids"]: # dont save if no examples left after filtering + _save_tokenized_batch_as_jsonl(file_path, filtered_tokenized_batch) + examples_counter += len(filtered_tokenized_batch["input_ids"]) batch = [] # last batch is smaller than config.tokenizer_batch_size, the "rest" @@ -175,6 +199,9 @@ def tokenize_and_save_fim_examples(config: Config, file_path: Path, fim_examples return_attention_mask=True ) tokenized_batch["labels"] = tokenized_batch["input_ids"] - _save_tokenized_batch_as_jsonl(file_path, tokenized_batch) + filtered_tokenized_batch = _filter_overlong_tokenized_examples(tokenized_batch, config.max_token_sequence_length) + if filtered_tokenized_batch["input_ids"]: # dont save if no examples left after filtering + _save_tokenized_batch_as_jsonl(file_path, filtered_tokenized_batch) + examples_counter += len(filtered_tokenized_batch["input_ids"]) - logger.info(f"Processed and saved {examples_counter} FIM examples to {file_path}") \ No newline at end of file + logger.info(f"Processed and saved {examples_counter} FIM examples to {file_path}") From cbe1f14f80d7643d86be71d2481f57dc09022813 Mon Sep 17 00:00:00 2001 From: cuolm Date: Fri, 1 May 2026 17:17:04 +0200 Subject: [PATCH 2/9] feat: add optional Unsloth training backend - Branch model loading into _load_hf_model (existing) and _load_unsloth_model (lazy import) - Unsloth uses use_gradient_checkpointing="unsloth" internally, disables HF Trainer gradient_checkpointing when active - Unsloth max_seq_length set to exact max_token_sequence_length for precise memory allocation - Full compatibility with existing merge_lora_and_save and GGUF conversion pipeline --- config/codefinetuner_config.yaml | 3 +- src/codefinetuner/finetune/config.py | 6 +++- src/codefinetuner/finetune/model.py | 47 ++++++++++++++++++++++++++-- src/codefinetuner/finetune/train.py | 3 +- 4 files changed, 53 insertions(+), 6 deletions(-) diff --git a/config/codefinetuner_config.yaml b/config/codefinetuner_config.yaml index 18f8521..401b906 100644 --- a/config/codefinetuner_config.yaml +++ b/config/codefinetuner_config.yaml @@ -9,6 +9,7 @@ globals: &globals fim_pad_token: "<|fim_pad|>" eos_token: "<|endoftext|>" label_pad_token_id: -100 + max_token_sequence_length: 1024 data_language: "c" data_extensions: [".c", ".h"] @@ -19,7 +20,6 @@ preprocess: train_ratio: 0.8 eval_ratio: 0.1 test_ratio: 0.1 - max_token_sequence_length: 1024 max_code_blocks_ast_depth: 2 min_middle_tokens_length: 20 max_middle_tokens_length: 200 @@ -33,6 +33,7 @@ preprocess: # Finetune stage finetune: <<: *globals + use_unsloth: True model_attn_implementation: "sdpa" lora_r: 32 lora_alpha: 64 diff --git a/src/codefinetuner/finetune/config.py b/src/codefinetuner/finetune/config.py index c98c28c..f395ab8 100644 --- a/src/codefinetuner/finetune/config.py +++ b/src/codefinetuner/finetune/config.py @@ -13,10 +13,14 @@ @dataclass class Config: -# --- Mandatory Parameters --- + # --- Mandatory Parameters --- model_name: str = MISSING fim_pad_token: str = MISSING label_pad_token_id: int = MISSING + max_token_sequence_length: int = MISSING + + # --- Unsloth Settings --- + use_unsloth: bool = False # --- Model Settings --- model_attn_implementation: str = "sdpa" # sdpa = built-in PyTorch implementation of scaled dot product attention, imporves performance and memory efficiency diff --git a/src/codefinetuner/finetune/model.py b/src/codefinetuner/finetune/model.py index 9d3fa6e..67eea81 100644 --- a/src/codefinetuner/finetune/model.py +++ b/src/codefinetuner/finetune/model.py @@ -1,4 +1,3 @@ - import logging from peft import LoraConfig, get_peft_model, prepare_model_for_kbit_training @@ -10,7 +9,14 @@ logger = logging.getLogger(__name__) -def load_and_configure_lora_model(config: Config) -> AutoModelForCausalLM: +def load_and_configure_lora_model(config: Config): + if config.use_unsloth: + return _load_unsloth_model(config) + else: + return _load_hf_model(config) + + +def _load_hf_model(config: Config) -> AutoModelForCausalLM: if config.device == "cuda": bnb_config = BitsAndBytesConfig( load_in_4bit=True, @@ -57,3 +63,40 @@ def load_and_configure_lora_model(config: Config) -> AutoModelForCausalLM: ) lora_model = get_peft_model(model, lora_config) return lora_model + + +def _load_unsloth_model(config: Config): + # Import Unsloth lazily here so its import-time patches only affect the CUDA/Unsloth + # finetuning path. Importing it at module level can monkey-patch transformers/peft + # process-wide, change behavior for non-Unsloth code paths, and add unnecessary import overhead. + try: + from unsloth import FastLanguageModel + except ImportError: + raise ImportError("Unsloth is not installed. Run: uv add unsloth or pip install unsloth") + + if config.device != "cuda": + raise RuntimeError("Unsloth requires CUDA. Either set use_unsloth=false or run on a CUDA device.") + + + model, _ = FastLanguageModel.from_pretrained( + model_name=config.model_name, + max_seq_length=config.max_token_sequence_length, + dtype=config.model_dtype, + load_in_4bit=True, + ) + + lora_model = FastLanguageModel.get_peft_model( + model, + lora_alpha=config.lora_alpha, + lora_dropout=config.lora_dropout, + r=config.lora_r, + bias=config.lora_bias, + target_modules=config.lora_target_modules, + use_gradient_checkpointing="unsloth" if config.trainer_gradient_checkpointing else False, + ) + + logger.info( + f"[Unsloth] Model: {config.model_name} | Device: {config.device} | " + f"Dtype: {config.model_dtype} | max_seq_length: {config.max_token_sequence_length}" + ) + return lora_model diff --git a/src/codefinetuner/finetune/train.py b/src/codefinetuner/finetune/train.py index 5aca17b..70b9ef3 100644 --- a/src/codefinetuner/finetune/train.py +++ b/src/codefinetuner/finetune/train.py @@ -2,7 +2,6 @@ import json import logging import shutil -from pathlib import Path from typing import Dict, List import matplotlib.pyplot as plt @@ -88,7 +87,7 @@ def train_lora_model( save_steps=config.trainer_save_steps, bf16=trainer_bf16, fp16=trainer_fp16, - gradient_checkpointing=config.trainer_gradient_checkpointing + gradient_checkpointing=(config.trainer_gradient_checkpointing and not config.use_unsloth), ) data_collator = FIMDataCollator( From a970cb6eca21f1c535c4a406e91bbca7e5a7592d Mon Sep 17 00:00:00 2001 From: cuolm Date: Mon, 4 May 2026 09:14:02 +0200 Subject: [PATCH 3/9] tests: add unsloth model loading tests --- tests/config/codefinetuner_config.yaml | 2 +- tests/finetune/test_model.py | 78 ++++++++++++++++++++++---- 2 files changed, 67 insertions(+), 13 deletions(-) diff --git a/tests/config/codefinetuner_config.yaml b/tests/config/codefinetuner_config.yaml index c2fb4b4..f727863 100644 --- a/tests/config/codefinetuner_config.yaml +++ b/tests/config/codefinetuner_config.yaml @@ -7,13 +7,13 @@ globals: &globals fim_pad_token: "<|fim_pad|>" eos_token: "<|endoftext|>" label_pad_token_id: -100 + max_token_sequence_length: 1024 data_language: "c" data_extensions: [".c", ".h"] preprocess: <<: *globals split_mode: "manual" - max_token_sequence_length: 1024 min_middle_tokens_length: 1 max_middle_tokens_length: 500 fim_examples_per_subblock_ratio: 1.0 diff --git a/tests/finetune/test_model.py b/tests/finetune/test_model.py index 34a69f6..8344a76 100644 --- a/tests/finetune/test_model.py +++ b/tests/finetune/test_model.py @@ -1,7 +1,5 @@ import pathlib -import json import pytest -import torch from datasets import IterableDataset from transformers import AutoTokenizer @@ -10,7 +8,9 @@ from codefinetuner.finetune.config import Config from codefinetuner.finetune.model import ( - load_and_configure_lora_model + load_and_configure_lora_model, + _load_hf_model, + _load_unsloth_model ) @@ -25,17 +25,37 @@ def config() -> Config: # --- load_and_configure_lora_model --- -def test_load_and_configure_lora_model_cuda(config, mocker): - # force CUDA path to test quantization and kbit preparation logic +def test_load_and_configure_lora_model_dispatches_to_hf(config, mocker): + config.use_unsloth = False + + hf_mock = mocker.patch("codefinetuner.finetune.model._load_hf_model") + load_and_configure_lora_model(config) + + hf_mock.assert_called_once_with(config) + + +def test_load_and_configure_lora_model_dispatches_to_unsloth(config, mocker): + config.use_unsloth = True + + unsloth_mock = mocker.patch("codefinetuner.finetune.model._load_unsloth_model") + load_and_configure_lora_model(config) + + unsloth_mock.assert_called_once_with(config) + + +# --- _load_hf_model --- + +def test_load_hf_model_cuda(config, mocker): config.device = "cuda" - + config.use_unsloth = False + bnb_mock = mocker.patch("codefinetuner.finetune.model.BitsAndBytesConfig") auto_model_mock = mocker.patch("codefinetuner.finetune.model.AutoModelForCausalLM.from_pretrained") kbit_prep_mock = mocker.patch("codefinetuner.finetune.model.prepare_model_for_kbit_training") lora_cfg_mock = mocker.patch("codefinetuner.finetune.model.LoraConfig") get_peft_mock = mocker.patch("codefinetuner.finetune.model.get_peft_model") - load_and_configure_lora_model(config) + _load_hf_model(config) bnb_mock.assert_called_once() auto_model_mock.assert_called_once() @@ -44,13 +64,15 @@ def test_load_and_configure_lora_model_cuda(config, mocker): get_peft_mock.assert_called_once() -def test_load_and_configure_lora_model_mps(config, mocker): +def test_load_hf_model_mps(config, mocker): config.device = "mps" + config.use_unsloth = False + auto_model_mock = mocker.patch("codefinetuner.finetune.model.AutoModelForCausalLM.from_pretrained") lora_cfg_mock = mocker.patch("codefinetuner.finetune.model.LoraConfig") get_peft_mock = mocker.patch("codefinetuner.finetune.model.get_peft_model") - load_and_configure_lora_model(config) + _load_hf_model(config) auto_model_mock.assert_called_once() auto_model_mock.return_value.to.assert_called_once_with("mps") @@ -58,15 +80,47 @@ def test_load_and_configure_lora_model_mps(config, mocker): get_peft_mock.assert_called_once() -def test_load_and_configure_lora_model_cpu(config, mocker): +def test_load_hf_model_cpu(config, mocker): config.device = "cpu" + config.use_unsloth = False + auto_model_mock = mocker.patch("codefinetuner.finetune.model.AutoModelForCausalLM.from_pretrained") lora_cfg_mock = mocker.patch("codefinetuner.finetune.model.LoraConfig") get_peft_mock = mocker.patch("codefinetuner.finetune.model.get_peft_model") - load_and_configure_lora_model(config) + _load_hf_model(config) auto_model_mock.assert_called_once() auto_model_mock.return_value.to.assert_called_once_with("cpu") lora_cfg_mock.assert_called_once() - get_peft_mock.assert_called_once() \ No newline at end of file + get_peft_mock.assert_called_once() + + +# --- load_unsloth_model --- + +def test_load_unsloth_model(config, mocker): + config.device = "cuda" + config.use_unsloth = True + + # Mock the unsloth module in sys.modules + mock_unsloth = mocker.MagicMock() + mocker.patch.dict("sys.modules", {"unsloth": mock_unsloth}) + + # FastLanguageModel.from_pretrained returns a tuple: (model, tokenizer) + mock_model = mocker.MagicMock() + mock_unsloth.FastLanguageModel.from_pretrained.return_value = (mock_model, None) + + load_and_configure_lora_model(config) + + mock_unsloth.FastLanguageModel.from_pretrained.assert_called_once() + mock_unsloth.FastLanguageModel.get_peft_model.assert_called_once() + + +def test_load_unsloth_model_non_cuda(config, mocker): + config.device = "cuda" + config.use_unsloth = True + + mocker.patch.dict("sys.modules", {"unsloth": None}) + + with pytest.raises(ImportError, match="Unsloth is not installed"): + load_and_configure_lora_model(config) From 5f437ef93999a626dc98f6923b116c00cf65d0b4 Mon Sep 17 00:00:00 2001 From: cuolm Date: Mon, 4 May 2026 09:52:56 +0200 Subject: [PATCH 4/9] tests: add required max_token_sequence_length to textwrap config tests --- tests/finetune/test_config.py | 1 + tests/preprocess/test_config.py | 3 +++ 2 files changed, 4 insertions(+) diff --git a/tests/finetune/test_config.py b/tests/finetune/test_config.py index 5ca3b70..8fa4026 100644 --- a/tests/finetune/test_config.py +++ b/tests/finetune/test_config.py @@ -50,6 +50,7 @@ def test_load_from_yaml_ignores_unknown_keys(tmp_path): fim_pad_token: "<|fim_pad|>" eos_token: "<|endoftext|>" label_pad_token_id: -100 + max_token_sequence_length: 1024 data_language: "c" data_extensions: [".c", ".h"] unknown_key_that_does_not_exist: 999 diff --git a/tests/preprocess/test_config.py b/tests/preprocess/test_config.py index 195a887..90d4879 100644 --- a/tests/preprocess/test_config.py +++ b/tests/preprocess/test_config.py @@ -52,6 +52,7 @@ def test_load_from_yaml_ignores_unknown_keys(tmp_path): fim_suffix_token: "<|fim_suffix|>" fim_pad_token: "<|fim_pad|>" eos_token: "<|endoftext|>" + max_token_sequence_length: 1024 data_language: "c" data_extensions: [".c"] unknown_key_that_does_not_exist: 999 @@ -74,6 +75,7 @@ def test_invalid_ratio_raises(tmp_path): fim_suffix_token: "<|fim_suffix|>" fim_pad_token: "<|fim_pad|>" eos_token: "<|endoftext|>" + max_token_sequence_length: 1024 data_language: "c" data_extensions: [".c"] train_ratio: 0.8 @@ -121,6 +123,7 @@ def test_unknown_language_raises(tmp_path): fim_suffix_token: "<|fim_suffix|>" fim_pad_token: "<|fim_pad|>" eos_token: "<|endoftext|>" + max_token_sequence_length: 1024 data_language: "unknown" data_extensions: [".unknown"] """) From 7f19a8118129613c0e1df61b3bc78c30f7551814 Mon Sep 17 00:00:00 2001 From: cuolm Date: Mon, 4 May 2026 09:55:36 +0200 Subject: [PATCH 5/9] build: add unsloth optional dependency with linux/win32 platform markers --- pyproject.toml | 1 + uv.lock | 893 +++++++++++++++++++++++++++++++++++++++---------- 2 files changed, 714 insertions(+), 180 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 1a95f82..42c7bda 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -35,6 +35,7 @@ dependencies = [ "omegaconf>=2.3.0", "gguf>=0.18.0", "sentencepiece>=0.2.1", + "unsloth>=2026.4.8 ; sys_platform == 'linux' or sys_platform == 'win32'", ] [dependency-groups] diff --git a/uv.lock b/uv.lock index 737c93d..c0d6f4e 100644 --- a/uv.lock +++ b/uv.lock @@ -21,7 +21,8 @@ dependencies = [ { name = "psutil" }, { name = "pyyaml" }, { name = "safetensors" }, - { name = "torch" }, + { name = "torch", version = "2.10.0", source = { registry = "https://pypi.org/simple" }, marker = "sys_platform != 'emscripten'" }, + { name = "torch", version = "2.11.0", source = { registry = "https://pypi.org/simple" }, marker = "sys_platform == 'emscripten'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/ca/14/787e5498cd062640f0f3d92ef4ae4063174f76f9afd29d13fc52a319daae/accelerate-1.13.0.tar.gz", hash = "sha256:d631b4e0f5b3de4aff2d7e9e6857d164810dfc3237d54d017f075122d057b236", size = 402835, upload-time = 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5f742ddf0a0b2418a5c13980896d32d8089c982a Mon Sep 17 00:00:00 2001 From: cuolm Date: Tue, 5 May 2026 11:42:18 +0000 Subject: [PATCH 6/9] fix: handle empty subblocks and remove truncation causing UTF-8 errors MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Empty subblocks caused np.random.choice(0, size=1) ValueError crash. Added early return [] when len(subblock_ranges) == 0. This is safe because empty blocks cannot generate FIM examples. Code block truncation code_block_utf8[:max_bytes_per_subblock] cut Tree-sitter nodes mid-Unicode (box chars █=e2 96 88 → e2 96), causing UnicodeDecodeError at 512-token limit. Removed truncation. This is safe because tokenizer post-filters overlong examples. --- src/codefinetuner/preprocess/process.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/codefinetuner/preprocess/process.py b/src/codefinetuner/preprocess/process.py index c98f332..c36b562 100644 --- a/src/codefinetuner/preprocess/process.py +++ b/src/codefinetuner/preprocess/process.py @@ -79,6 +79,8 @@ def _generate_fim_examples_from_code_block(config: Config, code_utf8: bytes, sub eos_token_utf8 = config.eos_token.encode('utf8') num_of_subblocks = len(subblock_ranges) + if num_of_subblocks == 0: + return [] num_of_fim_examples = max(1, int(num_of_subblocks * config.fim_examples_per_subblock_ratio)) unique_random_subblock_indices = config.rng.choice(len(subblock_ranges), size=num_of_fim_examples, replace=False) @@ -126,8 +128,6 @@ def create_fim_examples(config: Config, code_blocks_iter: Iterator[Tuple[bytes, subblock_ranges = _filter_subblocks(subblock_ranges, max_bytes_per_subblock) - code_block_utf8 = code_block_utf8[:max_bytes_per_subblock] # trunctate code block code if it is larger than bytes_per_code_block, we only consider subblocks inside this range. - fim_examples = _generate_fim_examples_from_code_block(config, code_block_utf8, subblock_ranges, bytes_per_token_ratio) for fim_example in fim_examples: yield fim_example From 005c75d267805821318c11c4758339796d4d9004 Mon Sep 17 00:00:00 2001 From: cuolm Date: Wed, 6 May 2026 06:13:56 +0000 Subject: [PATCH 7/9] chore: add script for token lenght analysis of dataset --- scripts/analyze_dataset.py | 37 +++++++++++++++++++++++++++++++++++++ 1 file changed, 37 insertions(+) create mode 100644 scripts/analyze_dataset.py diff --git a/scripts/analyze_dataset.py b/scripts/analyze_dataset.py new file mode 100644 index 0000000..aec05e9 --- /dev/null +++ b/scripts/analyze_dataset.py @@ -0,0 +1,37 @@ +import json + +def analyze_token_lengths(file_path, threshold): + max_len = 0 + total_count = 0 + under_threshold_count = 0 + + try: + with open(file_path, "r", encoding="utf-8") as f: + for line in f: + if not line.strip(): + continue + + total_count += 1 + data = json.loads(line) + current_len = len(data.get("input_ids", [])) + + if current_len > max_len: + max_len = current_len + + if current_len <= threshold: + under_threshold_count += 1 + + except FileNotFoundError: + print(f"Error: File '{file_path}' not found.") + return + + print(f"Total examples: {total_count}") + print(f"Maximum token length: {max_len}") + print(f"Examples under/at threshold ({threshold}): {under_threshold_count} out of {total_count}") + +if __name__ == "__main__": + # CONFIGURATION + file_path = "outputs/preprocess/results/datasets/train_dataset.jsonl" + threshold = 512 + + analyze_token_lengths(file_path, threshold) \ No newline at end of file From edf46dd6254dde255dbd19a2a634dd823f895540 Mon Sep 17 00:00:00 2001 From: cuolm Date: Wed, 6 May 2026 06:16:48 +0000 Subject: [PATCH 8/9] chore: add unsloth compiled cache folder to gitignore --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 7c1f5df..ddc48f7 100644 --- a/.gitignore +++ b/.gitignore @@ -17,4 +17,5 @@ wheels/ /data/ backup/ base_models/ +unsloth_compiled_cache/ TODO.md From 5bfe4605bf4b85ac2d2a530e40ddcdcfd593bb7e Mon Sep 17 00:00:00 2001 From: cuolm Date: Wed, 6 May 2026 06:47:26 +0000 Subject: [PATCH 9/9] chore: update codefinetuner configuration parameters --- config/codefinetuner_config.yaml | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/config/codefinetuner_config.yaml b/config/codefinetuner_config.yaml index 401b906..73af53f 100644 --- a/config/codefinetuner_config.yaml +++ b/config/codefinetuner_config.yaml @@ -2,21 +2,21 @@ # Shared across all stages globals: &globals workspace_path: null # null: defaults to current working directory (CWD) - model_name: "Qwen/Qwen2.5-0.5B" + model_name: "Qwen/Qwen2.5-Coder-0.5B" fim_prefix_token: "<|fim_prefix|>" fim_middle_token: "<|fim_middle|>" fim_suffix_token: "<|fim_suffix|>" fim_pad_token: "<|fim_pad|>" eos_token: "<|endoftext|>" label_pad_token_id: -100 - max_token_sequence_length: 1024 + max_token_sequence_length: 512 data_language: "c" data_extensions: [".c", ".h"] # Preprocess stage preprocess: <<: *globals - split_mode: "manual" + split_mode: "auto" train_ratio: 0.8 eval_ratio: 0.1 test_ratio: 0.1 @@ -25,7 +25,7 @@ preprocess: max_middle_tokens_length: 200 fim_examples_per_subblock_ratio: 1.0 tokenizer_batch_size: 32 - raw_data_path: "data/data_embedded" # null: defaults to /data + raw_data_path: null # null: defaults to /data tree_sitter_parser_path: null # null: uses tree_sitter_language_pack parser tree_sitter_definitions_path: null # null: uses package internal tree sitter definitions rng_seed: 0 @@ -37,26 +37,26 @@ finetune: model_attn_implementation: "sdpa" lora_r: 32 lora_alpha: 64 - lora_dropout: 0.1 + lora_dropout: 0.0 lora_bias: "none" lora_target_modules: ["q_proj", "v_proj", "k_proj", "o_proj", "gate_proj", "down_proj", "up_proj"] trainer_resume_from_checkpoint: null # null->fresh start, "last"->take last checkpoint trainer_clear_checkpoint_dir: false trainer_num_train_epochs: 1 - trainer_per_device_train_batch_size: 2 - trainer_per_device_eval_batch_size: 2 - trainer_gradient_accumulation_steps: 32 - trainer_learning_rate: 2e-5 - trainer_weight_decay: 0.1 + trainer_per_device_train_batch_size: 4 + trainer_per_device_eval_batch_size: 4 + trainer_gradient_accumulation_steps: 16 + trainer_learning_rate: 2e-4 + trainer_weight_decay: 0.01 trainer_max_grad_norm: 1.0 trainer_lr_scheduler_type: "cosine" trainer_warmup_steps: 50 trainer_gradient_checkpointing: true trainer_logging_steps: 10 trainer_eval_strategy: "steps" - trainer_eval_steps: 100 + trainer_eval_steps: 50 trainer_save_strategy: "steps" - trainer_save_steps: 100 + trainer_save_steps: 50 trainer_logging_strategy: "steps" dataset_shuffle_buffer_size: 50000 dataset_shuffle_seed: 0