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---
library_name: peft
license: other
base_model: unsloth/Llama-3.2-3B-Instruct
tags:
- llama-factory
- lora
- unsloth
- generated_from_trainer
model-index:
- name: llm3br256
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. -->
# llm3br256
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 centime dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0070
## 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: 48
- eval_batch_size: 48
- seed: 42
- 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
- num_epochs: 25.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1159 | 0.1208 | 25 | 0.1004 |
| 0.0843 | 0.2415 | 50 | 0.0635 |
| 0.0763 | 0.3623 | 75 | 0.0474 |
| 0.0496 | 0.4831 | 100 | 0.0365 |
| 0.046 | 0.6039 | 125 | 0.0316 |
| 0.0368 | 0.7246 | 150 | 0.0266 |
| 0.0283 | 0.8454 | 175 | 0.0232 |
| 0.0237 | 0.9662 | 200 | 0.0212 |
| 0.0234 | 1.0870 | 225 | 0.0194 |
| 0.0232 | 1.2077 | 250 | 0.0176 |
| 0.0307 | 1.3285 | 275 | 0.0178 |
| 0.0228 | 1.4493 | 300 | 0.0147 |
| 0.0167 | 1.5700 | 325 | 0.0155 |
| 0.0238 | 1.6908 | 350 | 0.0125 |
| 0.0191 | 1.8116 | 375 | 0.0138 |
| 0.0273 | 1.9324 | 400 | 0.0120 |
| 0.0194 | 2.0531 | 425 | 0.0125 |
| 0.0125 | 2.1739 | 450 | 0.0128 |
| 0.0132 | 2.2947 | 475 | 0.0117 |
| 0.0142 | 2.4155 | 500 | 0.0099 |
| 0.0119 | 2.5362 | 525 | 0.0105 |
| 0.0131 | 2.6570 | 550 | 0.0118 |
| 0.0089 | 2.7778 | 575 | 0.0100 |
| 0.0158 | 2.8986 | 600 | 0.0096 |
| 0.0119 | 3.0193 | 625 | 0.0096 |
| 0.0097 | 3.1401 | 650 | 0.0099 |
| 0.0089 | 3.2609 | 675 | 0.0092 |
| 0.0087 | 3.3816 | 700 | 0.0088 |
| 0.0083 | 3.5024 | 725 | 0.0088 |
| 0.0088 | 3.6232 | 750 | 0.0080 |
| 0.0058 | 3.7440 | 775 | 0.0069 |
| 0.008 | 3.8647 | 800 | 0.0070 |
| 0.0099 | 3.9855 | 825 | 0.0073 |
| 0.0072 | 4.1063 | 850 | 0.0113 |
| 0.0065 | 4.2271 | 875 | 0.0107 |
| 0.0079 | 4.3478 | 900 | 0.0097 |
| 0.0081 | 4.4686 | 925 | 0.0103 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3 |