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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 akoul_whitehorseliquidity_25c dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0008
## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.0078 | 0.0808 | 25 | 0.0079 |
| 0.0119 | 0.1616 | 50 | 0.0051 |
| 0.0036 | 0.2424 | 75 | 0.0032 |
| 0.004 | 0.3232 | 100 | 0.0025 |
| 0.0019 | 0.4040 | 125 | 0.0020 |
| 0.0021 | 0.4848 | 150 | 0.0018 |
| 0.0016 | 0.5657 | 175 | 0.0016 |
| 0.0013 | 0.6465 | 200 | 0.0015 |
| 0.0017 | 0.7273 | 225 | 0.0015 |
| 0.0015 | 0.8081 | 250 | 0.0014 |
| 0.0023 | 0.8889 | 275 | 0.0013 |
| 0.0012 | 0.9697 | 300 | 0.0013 |
| 0.0011 | 1.0505 | 325 | 0.0013 |
| 0.0011 | 1.1313 | 350 | 0.0013 |
| 0.0009 | 1.2121 | 375 | 0.0012 |
| 0.0015 | 1.2929 | 400 | 0.0011 |
| 0.0025 | 1.3737 | 425 | 0.0011 |
| 0.0016 | 1.4545 | 450 | 0.0011 |
| 0.001 | 1.5354 | 475 | 0.0011 |
| 0.0007 | 1.6162 | 500 | 0.0011 |
| 0.0008 | 1.6970 | 525 | 0.0011 |
| 0.001 | 1.7778 | 550 | 0.0010 |
| 0.0007 | 1.8586 | 575 | 0.0010 |
| 0.0013 | 1.9394 | 600 | 0.0009 |
| 0.0007 | 2.0202 | 625 | 0.0010 |
| 0.0006 | 2.1010 | 650 | 0.0009 |
| 0.0007 | 2.1818 | 675 | 0.0009 |
| 0.001 | 2.2626 | 700 | 0.0009 |
| 0.0015 | 2.3434 | 725 | 0.0009 |
| 0.0012 | 2.4242 | 750 | 0.0010 |
| 0.0012 | 2.5051 | 775 | 0.0009 |
| 0.0015 | 2.5859 | 800 | 0.0010 |
| 0.0011 | 2.6667 | 825 | 0.0009 |
| 0.0007 | 2.7475 | 850 | 0.0009 |
| 0.0009 | 2.8283 | 875 | 0.0009 |
| 0.0009 | 2.9091 | 900 | 0.0008 |
| 0.001 | 2.9899 | 925 | 0.0009 |
| 0.0006 | 3.0707 | 950 | 0.0009 |
| 0.0006 | 3.1515 | 975 | 0.0009 |
| 0.0007 | 3.2323 | 1000 | 0.0009 |
| 0.0004 | 3.3131 | 1025 | 0.0009 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3 |