---
library_name: peft
license: llama3.2
base_model: unsloth/Llama-3.2-1B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: miner_id_1_383a850e-bb15-45a2-8f4b-fc96eb001a74_1729770655
results: []
---
[
](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config
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:
- path: mhenrichsen/alpaca_2k_test
type: alpaca
debug: null
deepspeed: null
early_stopping_patience: 3
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: 1
gradient_checkpointing: true
group_by_length: false
hub_model_id: besimray/miner_id_1_383a850e-bb15-45a2-8f4b-fc96eb001a74_1729770655
hub_strategy: checkpoint
hub_token: null
learning_rate: 2.0e-05
load_in_4bit: false
load_in_8bit: true
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_steps: 10000
micro_batch_size: 10
mlflow_experiment_name: mhenrichsen/alpaca_2k_test
model_type: LlamaForCausalLM
num_epochs: 5
optimizer: adamw_bnb_8bit
output_dir: miner_id_besimray
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 5
save_strategy: steps
sequence_len: 4096
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0.05
wandb_entity: besimray24-rayon
wandb_mode: online
wandb_project: Public_TuningSN
wandb_run: miner_id_24
wandb_runid: 383a850e-bb15-45a2-8f4b-fc96eb001a74
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
```
# miner_id_1_383a850e-bb15-45a2-8f4b-fc96eb001a74_1729770655
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: 1.1623
## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 950
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3316 | 0.0053 | 1 | 1.2586 |
| 1.1351 | 0.0263 | 5 | 1.2596 |
| 1.2604 | 0.0526 | 10 | 1.2566 |
| 1.5396 | 0.0789 | 15 | 1.2454 |
| 1.4895 | 0.1053 | 20 | 1.2336 |
| 1.1625 | 0.1316 | 25 | 1.2236 |
| 1.3554 | 0.1579 | 30 | 1.2150 |
| 1.3275 | 0.1842 | 35 | 1.2100 |
| 1.1912 | 0.2105 | 40 | 1.2058 |
| 1.2335 | 0.2368 | 45 | 1.2030 |
| 1.0253 | 0.2632 | 50 | 1.1979 |
| 1.1242 | 0.2895 | 55 | 1.1970 |
| 0.9963 | 0.3158 | 60 | 1.1910 |
| 1.0977 | 0.3421 | 65 | 1.1919 |
| 1.1263 | 0.3684 | 70 | 1.1880 |
| 1.2144 | 0.3947 | 75 | 1.1860 |
| 1.3055 | 0.4211 | 80 | 1.1839 |
| 1.1513 | 0.4474 | 85 | 1.1818 |
| 1.0702 | 0.4737 | 90 | 1.1819 |
| 1.2561 | 0.5 | 95 | 1.1797 |
| 1.1373 | 0.5263 | 100 | 1.1775 |
| 1.2136 | 0.5526 | 105 | 1.1780 |
| 1.3591 | 0.5789 | 110 | 1.1771 |
| 1.5703 | 0.6053 | 115 | 1.1744 |
| 1.1601 | 0.6316 | 120 | 1.1754 |
| 1.1412 | 0.6579 | 125 | 1.1748 |
| 1.1449 | 0.6842 | 130 | 1.1731 |
| 1.1706 | 0.7105 | 135 | 1.1736 |
| 1.0503 | 0.7368 | 140 | 1.1730 |
| 1.1938 | 0.7632 | 145 | 1.1730 |
| 1.4802 | 0.7895 | 150 | 1.1710 |
| 1.1359 | 0.8158 | 155 | 1.1688 |
| 1.3575 | 0.8421 | 160 | 1.1709 |
| 1.0188 | 0.8684 | 165 | 1.1685 |
| 1.147 | 0.8947 | 170 | 1.1684 |
| 0.9949 | 0.9211 | 175 | 1.1668 |
| 1.3082 | 0.9474 | 180 | 1.1673 |
| 1.1995 | 0.9737 | 185 | 1.1654 |
| 1.2346 | 1.0 | 190 | 1.1654 |
| 1.0948 | 1.0263 | 195 | 1.1660 |
| 1.3838 | 1.0526 | 200 | 1.1643 |
| 0.9594 | 1.0789 | 205 | 1.1644 |
| 1.1423 | 1.1053 | 210 | 1.1635 |
| 1.1774 | 1.1316 | 215 | 1.1645 |
| 1.0085 | 1.1579 | 220 | 1.1642 |
| 1.0912 | 1.1842 | 225 | 1.1611 |
| 1.193 | 1.2105 | 230 | 1.1627 |
| 1.2437 | 1.2368 | 235 | 1.1640 |
| 1.1814 | 1.2632 | 240 | 1.1623 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1