---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
tags:
- axolotl
- base_model:adapter:Qwen/Qwen2.5-Coder-7B-Instruct
- lora
- transformers
- roblox
- luau
datasets:
- darwinkernelpanic/luau_corpus_axolotl
pipeline_tag: text-generation
model-index:
- name: Qwen2.5-Coder-7B-Instruct-Luau
results: []
---
[
](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config
axolotl version: `0.13.0.dev0`
```yaml
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
# Auto-upload to HuggingFace when done
hub_model_id: darwinkernelpanic/Qwen2.5-Coder-7B-Instruct-Luau # Change this to your HF username
hub_strategy: every_save # Uploads checkpoints as you train
trust_remote_code: true
load_in_8bit: false
load_in_4bit: true
datasets:
- path: darwinkernelpanic/luau_corpus_axolotl
type: completion
field_instruction: text # Check the actual column names on HF
field_output: completion # Might be "text" or "code" — verify first
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/qwen-luau-finetune
sequence_len: 2048
sample_packing: true
eval_sample_packing: true
adapter: qlora
lora_model_dir:
lora_r: 64
lora_alpha: 64
lora_dropout: 0.05
lora_target_linear: true
# Weights & Biases tracking (optional but clutch)
wandb_project: qwen-luau-finetune
wandb_entity:
wandb_watch:
wandb_name: qwen2.5-coder-7b-luau
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 3
optimizer: adamw_torch_fused
lr_scheduler: cosine
learning_rate: 0.0003
bf16: auto
tf32: true
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
resume_from_checkpoint:
logging_steps: 10
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch: 4
saves_per_epoch: 1
weight_decay: 0.01
fsdp:
- full_shard
- auto_wrap
fsdp_config:
fsdp_limit_all_gathers: true
fsdp_sync_module_states: true
fsdp_offload_params: false
fsdp_use_orig_params: false
fsdp_cpu_ram_efficient_loading: true
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
fsdp_sharding_strategy: FULL_SHARD
fsdp_state_dict_type: FULL_STATE_DICT
special_tokens:
pad_token: "<|endoftext|>"
```
# Qwen2.5-Coder-7B-Instruct-Luau
This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) on the darwinkernelpanic/luau_corpus_axolotl dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Ppl: nan
- Memory/max Active (gib): 14.12
- Memory/max Allocated (gib): 14.01
- Memory/device Reserved (gib): 14.69
## Model description
The model was fine-tuned on the Roblox/luau_corpus dataset which was converted to have the "prompt" collum replaced by "text" for compatibility reasons.
It was fine-tuned for improved knowledge and performance on Luau code (Roblox's Lua dialect, see [luau.org](https://luau.org)), which should end up improving code quality for Luau and Roblox projects.
## Intended uses & limitations
This model is intended for use within applications that use the Luau programming language, including but not limited to
- Roblox projects
- Standalone Luau projects (Lune?)
It may have limitations for projects that
- Use alternative languages
- Use Lua
- Non programming related projects
## Training and evaluation data
N/A
## Training procedure
Trained on 2x NVIDIA RTX 4090s
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 105
### Training results
| Training Loss | Epoch | Step | Validation Loss | Ppl | Active (gib) | Allocated (gib) | Reserved (gib) |
|:-------------:|:------:|:----:|:---------------:|:------:|:------------:|:---------------:|:--------------:|
| No log | 0 | 0 | 3.9969 | 54.428 | 11.21 | 11.1 | 12.26 |
| No log | 0.2535 | 9 | nan | nan | 14.12 | 14.01 | 15.56 |
| 12.4054 | 0.5070 | 18 | nan | nan | 14.12 | 14.01 | 14.69 |
| 0.0 | 0.7606 | 27 | nan | nan | 14.12 | 14.01 | 14.69 |
| 0.0 | 1.0 | 36 | nan | nan | 14.12 | 14.01 | 14.69 |
| 0.0 | 1.2535 | 45 | nan | nan | 14.12 | 14.01 | 14.69 |
| 0.0 | 1.5070 | 54 | nan | nan | 14.12 | 14.01 | 14.69 |
| 0.0 | 1.7606 | 63 | nan | nan | 14.12 | 14.01 | 14.69 |
| 0.0 | 2.0 | 72 | nan | nan | 14.12 | 14.01 | 14.69 |
| 0.0 | 2.2535 | 81 | nan | nan | 14.12 | 14.01 | 14.69 |
| 0.0 | 2.5070 | 90 | nan | nan | 11.83 | 11.72 | 14.69 |
| 0.0 | 2.7606 | 99 | nan | nan | 14.12 | 14.01 | 14.69 |
### Framework versions
- PEFT 0.18.0
- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1