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---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-3B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: qlora-llama3b-iterative
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. -->
# qlora-llama3b-iterative
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the train-iterative dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0051
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.1156 | 0.0889 | 10 | 1.5894 |
| 1.1893 | 0.1778 | 20 | 0.6868 |
| 0.5218 | 0.2667 | 30 | 0.4555 |
| 0.5292 | 0.3556 | 40 | 0.3795 |
| 0.3866 | 0.4444 | 50 | 0.3065 |
| 0.3232 | 0.5333 | 60 | 0.2074 |
| 0.1802 | 0.6222 | 70 | 0.1532 |
| 0.21 | 0.7111 | 80 | 0.1348 |
| 0.158 | 0.8 | 90 | 0.1372 |
| 0.1629 | 0.8889 | 100 | 0.1276 |
| 0.0966 | 0.9778 | 110 | 0.1003 |
| 0.0643 | 1.0667 | 120 | 0.0879 |
| 0.0726 | 1.1556 | 130 | 0.0872 |
| 0.0493 | 1.2444 | 140 | 0.0906 |
| 0.0746 | 1.3333 | 150 | 0.0587 |
| 0.0473 | 1.4222 | 160 | 0.0561 |
| 0.0644 | 1.5111 | 170 | 0.0503 |
| 0.0366 | 1.6 | 180 | 0.0307 |
| 0.0247 | 1.6889 | 190 | 0.0233 |
| 0.01 | 1.7778 | 200 | 0.0215 |
| 0.0393 | 1.8667 | 210 | 0.0122 |
| 0.0299 | 1.9556 | 220 | 0.0180 |
| 0.0166 | 2.0444 | 230 | 0.0082 |
| 0.0319 | 2.1333 | 240 | 0.0083 |
| 0.0077 | 2.2222 | 250 | 0.0072 |
| 0.0141 | 2.3111 | 260 | 0.0031 |
| 0.0017 | 2.4 | 270 | 0.0120 |
| 0.0015 | 2.4889 | 280 | 0.0153 |
| 0.0126 | 2.5778 | 290 | 0.0141 |
| 0.0043 | 2.6667 | 300 | 0.0022 |
| 0.0068 | 2.7556 | 310 | 0.0019 |
| 0.0018 | 2.8444 | 320 | 0.0022 |
| 0.0026 | 2.9333 | 330 | 0.0034 |
| 0.0017 | 3.0222 | 340 | 0.0076 |
| 0.0002 | 3.1111 | 350 | 0.0102 |
| 0.0004 | 3.2 | 360 | 0.0112 |
| 0.006 | 3.2889 | 370 | 0.0094 |
| 0.0003 | 3.3778 | 380 | 0.0075 |
| 0.0003 | 3.4667 | 390 | 0.0069 |
| 0.0002 | 3.5556 | 400 | 0.0067 |
| 0.0005 | 3.6444 | 410 | 0.0066 |
| 0.0003 | 3.7333 | 420 | 0.0072 |
| 0.0037 | 3.8222 | 430 | 0.0063 |
| 0.004 | 3.9111 | 440 | 0.0053 |
| 0.0003 | 4.0 | 450 | 0.0052 |
| 0.0002 | 4.0889 | 460 | 0.0051 |
| 0.0002 | 4.1778 | 470 | 0.0050 |
| 0.0006 | 4.2667 | 480 | 0.0049 |
| 0.0005 | 4.3556 | 490 | 0.0048 |
| 0.0002 | 4.4444 | 500 | 0.0051 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |