---
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
datasets:
- felixwangg/prime_vul_minus_splitted
pipeline_tag: text-generation
model-index:
- name: u901/t577wang/SecSteer-v2/axolotl-outputs/lora/Qwen2.5-Coder-7B-func-stage1-insec-stage2-4k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.16.1`
```yaml
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
model_type: Qwen2ForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false

datasets:
  - path: felixwangg/prime_vul_minus_splitted
    type: chat_template
    split: train
test_datasets:
  - path: felixwangg/prime_vul_minus_splitted
    type: chat_template
    split: validation
dataset_prepared_path: /u901/t577wang/SecSteer-v2/axolotl-datasets/lora/Qwen2.5-Coder-7B/func-stage1-insec-stage2-4k
val_set_size: 0
output_dir: /u901/t577wang/SecSteer-v2/axolotl-outputs/lora/Qwen2.5-Coder-7B-func-stage1-insec-stage2-4k
sequence_len: 4096
sample_packing: false
eval_sample_packing: false
pad_to_sequence_len: true

adapter: lora
lora_model_dir: /u901/t577wang/SecSteer-v2/axolotl-outputs/lora/Qwen2.5-Coder-7B-func-stage1-4k/checkpoint-54
lora_r: 16
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
merge_lora: true

wandb_project: sft-primevul-sweep-ctx-0
wandb_entity: wtkuan
wandb_watch: "false"
wandb_name: Qwen2.5-Coder-7B-func-stage1-insec-stage2-4k
wandb_log_model: "false"


gradient_accumulation_steps: 8
micro_batch_size: 4
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 4e-5

bf16: true
tf32: false

train_on_inputs: false
roles_to_train: ['assistant']

gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: true

num_epochs: 1
warmup_ratio: 0.1
early_stopping_patience: 1000
eval_steps: 15
save_steps: 15
save_total_limit: 1000
load_best_model_at_end: true

weight_decay: 0.02
special_tokens:

plugins:

```

</details><br>

# u901/t577wang/SecSteer-v2/axolotl-outputs/lora/Qwen2.5-Coder-7B-func-stage1-insec-stage2-4k

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 felixwangg/prime_vul_minus_splitted dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6990
- Ppl: 2.0117
- Memory/max Active (gib): 38.14
- Memory/max Allocated (gib): 38.14
- Memory/device Reserved (gib): 51.89

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 5
- training_steps: 57

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Ppl    | Active (gib) | Allocated (gib) | Reserved (gib) |
|:-------------:|:------:|:----:|:---------------:|:------:|:------------:|:---------------:|:--------------:|
| No log        | 0      | 0    | 0.7468          | 2.1103 | 37.83        | 37.83           | 41.81          |
| 0.7253        | 0.2655 | 15   | 0.7130          | 2.0401 | 38.14        | 38.14           | 51.31          |
| 0.7463        | 0.5310 | 30   | 0.7029          | 2.0196 | 38.14        | 38.14           | 51.89          |
| 0.7018        | 0.7965 | 45   | 0.6994          | 2.0125 | 38.14        | 38.14           | 51.89          |
| 0.6523        | 1.0    | 57   | 0.6990          | 2.0117 | 38.14        | 38.14           | 51.89          |


### Framework versions

- PEFT 0.19.1
- Transformers 5.5.4
- Pytorch 2.11.0+cu130
- Datasets 4.5.0
- Tokenizers 0.22.2