---
library_name: peft
license: llama3.1
base_model: unsloth/Meta-Llama-3.1-8B-Instruct
tags:
- axolotl
- base_model:adapter:unsloth/Meta-Llama-3.1-8B-Instruct
- lora
- transformers
datasets:
- mx003/cve
pipeline_tag: text-generation
model-index:
- name: outputs/mymodel
  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: `0.13.0.dev0`
```yaml
adapter: lora
base_model: unsloth/Meta-Llama-3.1-8B-Instruct
bf16: true
fp16: false

datasets:
  - path: mx003/cve
    type: chat_template
    field_messages: messages

lora_r: 32
lora_alpha: 64
lora_dropout: 0.05
lora_target_modules:
  - q_proj
  - v_proj
  - k_proj
  - o_proj
  - gate_proj
  - down_proj
  - up_proj

gradient_accumulation_steps: 4
gradient_checkpointing: true
micro_batch_size: 2
num_epochs: 3
learning_rate: 0.0002
optimizer: adamw_torch
train_on_inputs: false
group_by_length: true

output_dir: ./outputs/mymodel
sequence_len: 4096
save_steps: 50
flash_attention: true
sample_packing: true
```

</details><br>

# outputs/mymodel

This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct) on the mx003/cve dataset.

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_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: 2
- training_steps: 66

### Training results



### Framework versions

- PEFT 0.17.1
- Transformers 4.57.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1