---
library_name: peft
license: other
base_model: unsloth/Qwen2.5-3B-Instruct
tags:
- generated_from_trainer
datasets:
- ICEPVP8977/Uncensored_Small_Test_Time_Compute
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: `0.8.0.dev0`
```yaml
adapter: lora
base_model: unsloth/Qwen2.5-3B-Instruct
bf16: auto
dataset_processes: 32
per_device_train_batch_size: 1
datasets:
- message_property_mappings:
    content: content
    role: role
  path: ICEPVP8977/Uncensored_Small_Test_Time_Compute
  type: alpaca
  trust_remote_code: false
gradient_accumulation_steps: 1
gradient_checkpointing: true
learning_rate: 0.0002
lisa_layers_attribute: model.layers
load_best_model_at_end: false
load_in_4bit: true
load_in_8bit: false
lora_alpha: 16
lora_dropout: 0.05
lora_r: 8
lora_target_modules:
- q_proj
- v_proj
- k_proj
- o_proj
- gate_proj
- down_proj
- up_proj
loraplus_lr_embedding: 1.0e-06
lr_scheduler: cosine
max_prompt_len: 512
mean_resizing_embeddings: false
micro_batch_size: 8
num_epochs: 1.0
optimizer: paged_adamw_8bit
output_dir: ./outputs/mymodel
pretrain_multipack_attn: true
pretrain_multipack_buffer_size: 10000
qlora_sharded_model_loading: false
ray_num_workers: 1
resources_per_worker:
  GPU: 1
sample_packing_bin_size: 200
sample_packing_group_size: 100000
save_only_model: false
save_safetensors: true
sequence_len: 4096
shuffle_merged_datasets: true
skip_prepare_dataset: false
strict: false
train_on_inputs: false
trl:
  log_completions: false
  ref_model_mixup_alpha: 0.9
  ref_model_sync_steps: 64
  sync_ref_model: false
  use_vllm: false
  vllm_device: auto
  vllm_dtype: auto
  vllm_gpu_memory_utilization: 0.9
use_ray: false
val_set_size: 0.0
weight_decay: 0.0

```

</details><br>

# outputs/mymodel

Fine-tuned version of [unsloth/Qwen2.5-3B-Instruct](https://huggingface.co/unsloth/Qwen2.5-3B-Instruct) on the ICEPVP8977/Uncensored_Small_Test_Time_Compute dataset.

This lora model will fully uncensor the qwen 2.5 3b model, use alpaca instruction template.