---
library_name: peft
license: llama3.2
base_model: unsloth/Llama-3.2-3B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 82da4164-7ca8-4b2e-82cb-cf077fe314f5
  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: `0.4.1`
```yaml
adapter: lora
base_model: unsloth/Llama-3.2-3B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - cfe4cfbd460d8124_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/cfe4cfbd460d8124_train_data.json
  type:
    field_input: OriginalAddress1
    field_instruction: PermitTypeDesc
    field_output: Description
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
device_map:
  ? ''
  : 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/82da4164-7ca8-4b2e-82cb-cf077fe314f5
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 2011
micro_batch_size: 4
mlflow_experiment_name: /tmp/cfe4cfbd460d8124_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 2048
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.04127830659875009
wandb_entity: null
wandb_mode: online
wandb_name: 1c0ec80c-26dd-4dfe-858e-1b40744d4a00
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 1c0ec80c-26dd-4dfe-858e-1b40744d4a00
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 82da4164-7ca8-4b2e-82cb-cf077fe314f5

This model is a fine-tuned version of [unsloth/Llama-3.2-3B](https://huggingface.co/unsloth/Llama-3.2-3B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4282

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: 10
- training_steps: 2011

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.5394        | 0.0003 | 1    | 4.5230          |
| 1.9022        | 0.0276 | 100  | 1.7936          |
| 1.6432        | 0.0551 | 200  | 1.7068          |
| 1.5876        | 0.0827 | 300  | 1.6605          |
| 1.7241        | 0.1102 | 400  | 1.6289          |
| 1.2011        | 0.1378 | 500  | 1.6054          |
| 1.5357        | 0.1653 | 600  | 1.5869          |
| 1.532         | 0.1929 | 700  | 1.5657          |
| 1.6306        | 0.2204 | 800  | 1.5495          |
| 1.7204        | 0.2480 | 900  | 1.5271          |
| 1.616         | 0.2755 | 1000 | 1.5105          |
| 1.4012        | 0.3031 | 1100 | 1.4984          |
| 1.6245        | 0.3307 | 1200 | 1.4835          |
| 1.4906        | 0.3582 | 1300 | 1.4692          |
| 1.6158        | 0.3858 | 1400 | 1.4579          |
| 1.5505        | 0.4133 | 1500 | 1.4491          |
| 1.5439        | 0.4409 | 1600 | 1.4409          |
| 1.5436        | 0.4684 | 1700 | 1.4351          |
| 1.6966        | 0.4960 | 1800 | 1.4305          |
| 1.387         | 0.5235 | 1900 | 1.4287          |
| 1.0875        | 0.5511 | 2000 | 1.4282          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1