---
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-ad9b0fa2-323a-4d04-be5e-1304b49c48da
  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/ad9b0fa2-323a-4d04-be5e-1304b49c48da.json
  ds_type: json
  path: /workspace/axolotl/data/ad9b0fa2-323a-4d04-be5e-1304b49c48da.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-ad9b0fa2-323a-4d04-be5e-1304b49c48da
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
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%2F20241024%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20241024T015513Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=0879a56693622d0d57a6f707ace9e2a5e73d3647c1a227a4016e3e4011effe25
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: ad9b0fa2-323a-4d04-be5e-1304b49c48da
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# tuning-miner-testbed-ad9b0fa2-323a-4d04-be5e-1304b49c48da

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: 0.7753

## 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
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8864        | 0.0095 | 1    | 0.9756          |
| 0.8585        | 0.4964 | 52   | 0.8117          |
| 0.7169        | 0.9928 | 104  | 0.7860          |
| 0.7558        | 1.4893 | 156  | 0.7723          |
| 0.7814        | 1.9857 | 208  | 0.7655          |
| 0.6849        | 2.4821 | 260  | 0.7670          |
| 0.7456        | 2.9785 | 312  | 0.7646          |
| 0.6037        | 3.4749 | 364  | 0.7706          |
| 0.6335        | 3.9714 | 416  | 0.7703          |
| 0.5835        | 4.4678 | 468  | 0.7749          |
| 0.7157        | 4.9642 | 520  | 0.7753          |


### Framework versions

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