---
library_name: peft
license: llama3.2
base_model: unsloth/Llama-3.2-3B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 5cc7e326-b0be-43e4-af92-aa4134de2dd3
  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-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 2473a580e21e684a_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/2473a580e21e684a_train_data.json
  type:
    field_input: ground_knowledge
    field_instruction: query
    field_output: hit_knowledge
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: oldiday/5cc7e326-b0be-43e4-af92-aa4134de2dd3
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_steps: 100
micro_batch_size: 8
mlflow_experiment_name: /tmp/2473a580e21e684a_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: techspear-hub
wandb_mode: online
wandb_name: bba600cc-9959-4989-96cb-bd88b8ecffb8
wandb_project: Gradients-On-Six
wandb_run: your_name
wandb_runid: bba600cc-9959-4989-96cb-bd88b8ecffb8
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 5cc7e326-b0be-43e4-af92-aa4134de2dd3

This model is a fine-tuned version of [unsloth/Llama-3.2-3B-Instruct](https://huggingface.co/unsloth/Llama-3.2-3B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6336

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0005 | 1    | 2.0430          |
| 2.0411        | 0.0042 | 9    | 2.0034          |
| 1.7498        | 0.0083 | 18   | 1.7798          |
| 1.7469        | 0.0125 | 27   | 1.7146          |
| 1.6712        | 0.0167 | 36   | 1.6825          |
| 1.6908        | 0.0208 | 45   | 1.6609          |
| 1.635         | 0.0250 | 54   | 1.6492          |
| 1.6188        | 0.0292 | 63   | 1.6416          |
| 1.6806        | 0.0333 | 72   | 1.6370          |
| 1.6951        | 0.0375 | 81   | 1.6343          |
| 1.696         | 0.0417 | 90   | 1.6338          |
| 1.5216        | 0.0458 | 99   | 1.6336          |


### Framework versions

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