---
library_name: peft
license: llama3.2
base_model: unsloth/Llama-3.2-3B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 1a43e5c4-855d-416a-b8ec-a2a916cb7907
  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:
  - 68ef826ced66c8c7_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/68ef826ced66c8c7_train_data.json
  type:
    field_input: input
    field_instruction: instruction
    field_output: output
    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: 400
eval_table_size: null
flash_attention: true
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/1a43e5c4-855d-416a-b8ec-a2a916cb7907
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: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
- down_proj
- up_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 7351
micro_batch_size: 2
mlflow_experiment_name: /tmp/68ef826ced66c8c7_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: 400
sequence_len: 2048
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.033916240452578315
wandb_entity: null
wandb_mode: online
wandb_name: f214522a-6979-41cd-a80c-d566c41b01d8
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: f214522a-6979-41cd-a80c-d566c41b01d8
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 1a43e5c4-855d-416a-b8ec-a2a916cb7907

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: 0.7412

## 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_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: 7351

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7224        | 0.0001 | 1    | 2.1008          |
| 0.8266        | 0.0225 | 400  | 0.8611          |
| 0.95          | 0.0449 | 800  | 0.8325          |
| 0.916         | 0.0674 | 1200 | 0.8323          |
| 0.9649        | 0.0899 | 1600 | 0.8187          |
| 1.0447        | 0.1123 | 2000 | 0.8094          |
| 0.9421        | 0.1348 | 2400 | 0.8086          |
| 0.759         | 0.1573 | 2800 | 0.8016          |
| 0.8835        | 0.1797 | 3200 | 0.7898          |
| 1.0793        | 0.2022 | 3600 | 0.7785          |
| 0.8628        | 0.2247 | 4000 | 0.7755          |
| 0.8557        | 0.2472 | 4400 | 0.7677          |
| 0.6361        | 0.2696 | 4800 | 0.7604          |
| 0.5638        | 0.2921 | 5200 | 0.7556          |
| 1.1077        | 0.3146 | 5600 | 0.7485          |
| 0.8949        | 0.3370 | 6000 | 0.7458          |
| 0.885         | 0.3595 | 6400 | 0.7437          |
| 1.1648        | 0.3820 | 6800 | 0.7415          |
| 1.0295        | 0.4044 | 7200 | 0.7412          |


### Framework versions

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