---
library_name: peft
license: llama3.2
base_model: unsloth/Llama-3.2-1B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: tuning-miner-testbed-asd
  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-3.2-1B-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
dataset_processes: 12
datasets:
- data_files:
  - /workspace/axolotl/data/asd.json
  ds_type: json
  path: /workspace/axolotl/data/asd.json
  type:
    field_input: problem
    field_instruction: type
    field_output: solution
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 512
eval_table_size: null
evals_per_epoch: 2
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: ncbateman/tuning-miner-testbed-asd
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: true
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
lr_scheduler: cosine
max_steps: 5
micro_batch_size: 4
mlflow_experiment_name: https://5a301a635a9d0ac3cb7fcc3bf373c3c3.r2.cloudflarestorage.com/tuning/lighteval/MATH-Hard_train_data.json?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=d49fdd0cc9750a097b58ba35b2d9fbed%2F20241023%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20241023T143154Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=4a7c1dcd761dd78a44d40f4535772b806d1b658d16321165e31f5e9b75617896
model_type: LlamaForCausalLM
num_epochs: 5
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: 20
save_strategy: steps
sequence_len: 4096
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0.05
wandb_entity: breakfasthut
wandb_mode: online
wandb_project: tuning-miner
wandb_run: miner
wandb_runid: asd
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# tuning-miner-testbed-asd

This model is a fine-tuned version of [unsloth/Llama-3.2-1B-Instruct](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9848

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9943        | 0.0103 | 1    | 0.9864          |
| 0.9017        | 0.0206 | 2    | 0.9887          |
| 1.1019        | 0.0309 | 3    | 0.9872          |
| 0.8137        | 0.0412 | 4    | 0.9864          |
| 0.9198        | 0.0515 | 5    | 0.9848          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1