---
library_name: peft
license: llama3.2
base_model: unsloth/Llama-3.2-1B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: miner1_60c4f9de-24ff-4eeb-a041-3c142f4f4888_1731086176
  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
datasets:
- data_files:
  - MATH-Hard_train_data.json
  ds_type: json
  path: /workspace/input_data/MATH-Hard_train_data.json
  type:
    field_input: solution
    field_instruction: type
    field_output: problem
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 5
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hours_to_complete: 4
hub_model_id: besimray/miner1_60c4f9de-24ff-4eeb-a041-3c142f4f4888_1731086176
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
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: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 500
micro_batch_size: 2
mlflow_experiment_name: /tmp/MATH-Hard_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 4
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: 10
save_strategy: steps
sequence_len: 4096
started_at: '2024-11-08T17:16:16.217205'
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: besimray24-rayon
wandb_mode: online
wandb_project: Public_TuningSN
wandb_run: miner_id_24
wandb_runid: 60c4f9de-24ff-4eeb-a041-3c142f4f4888
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# miner1_60c4f9de-24ff-4eeb-a041-3c142f4f4888_1731086176

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: 0.8877

## 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: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7576        | 0.0024 | 1    | 1.4666          |
| 1.191         | 0.0119 | 5    | 1.4214          |
| 0.4449        | 0.0239 | 10   | 1.1578          |
| 1.6707        | 0.0358 | 15   | 1.0529          |
| 0.9342        | 0.0477 | 20   | 1.0087          |
| 1.1447        | 0.0597 | 25   | 0.9941          |
| 1.331         | 0.0716 | 30   | 0.9711          |
| 0.9763        | 0.0835 | 35   | 0.9544          |
| 0.6841        | 0.0955 | 40   | 0.9494          |
| 0.7273        | 0.1074 | 45   | 0.9417          |
| 0.766         | 0.1193 | 50   | 0.9387          |
| 0.9841        | 0.1313 | 55   | 0.9331          |
| 0.8733        | 0.1432 | 60   | 0.9313          |
| 0.64          | 0.1551 | 65   | 0.9237          |
| 1.3638        | 0.1671 | 70   | 0.9212          |
| 0.8958        | 0.1790 | 75   | 0.9195          |
| 0.8923        | 0.1909 | 80   | 0.9134          |
| 1.1555        | 0.2029 | 85   | 0.9122          |
| 0.7069        | 0.2148 | 90   | 0.9102          |
| 0.9398        | 0.2267 | 95   | 0.9005          |
| 1.1527        | 0.2387 | 100  | 0.8966          |
| 1.0022        | 0.2506 | 105  | 0.8951          |
| 0.7001        | 0.2625 | 110  | 0.8915          |
| 0.6991        | 0.2745 | 115  | 0.8872          |
| 1.1245        | 0.2864 | 120  | 0.8851          |
| 1.0224        | 0.2983 | 125  | 0.8877          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.1
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.3