---
library_name: peft
license: bigcode-openrail-m
base_model: bigcode/starcoder2-15b
tags:
- generated_from_trainer
datasets:
- kevinwsbr/vulnfixes-web
model-index:
- name: outputs/starcoder-vulnfixes-web
  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: `0.8.0.dev0`
```yaml
base_model: bigcode/starcoder2-15b
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: kevinwsbr/vulnfixes-web
    type: alpaca


dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/starcoder-vulnfixes-web

adapter: qlora
lora_model_dir:

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: starcoder
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 2
num_epochs: 3
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 2e-5

train_on_inputs: false
group_by_length: false
bf16: auto
fp16: false
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 20
evals_per_epoch: 4
eval_steps:
eval_table_size:
saves_per_epoch: 4
save_steps:
save_total_limit: 2
debug:
deepspeed:
weight_decay:
fsdp:
fsdp_config:
special_tokens:
  pad_token: "<|endoftext|>"
  eos_token: "<|endoftext|>"

```

</details><br>

# outputs/starcoder-vulnfixes-web

This model is a fine-tuned version of [bigcode/starcoder2-15b](https://huggingface.co/bigcode/starcoder2-15b) on the kevinwsbr/vulnfixes-web dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0529

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 20
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1499        | 0.0092 | 1    | 0.0645          |
| 0.1554        | 0.2569 | 28   | 0.0622          |
| 0.0745        | 0.5138 | 56   | 0.0571          |
| 0.0616        | 0.7706 | 84   | 0.0559          |
| 0.0645        | 1.0275 | 112  | 0.0547          |
| 0.0601        | 1.2844 | 140  | 0.0542          |
| 0.0688        | 1.5413 | 168  | 0.0537          |
| 0.0424        | 1.7982 | 196  | 0.0534          |
| 0.086         | 2.0550 | 224  | 0.0532          |
| 0.0759        | 2.3119 | 252  | 0.0530          |
| 0.0583        | 2.5688 | 280  | 0.0529          |
| 0.1087        | 2.8257 | 308  | 0.0529          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0