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---
base_model: meta-llama/Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct-SAA-600
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. -->
# Llama-3.1-8B-Instruct-SAA-600
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the bct_non_cot_dpo_600 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0943
- Rewards/chosen: -0.0072
- Rewards/rejected: -0.0623
- Rewards/accuracies: 0.8833
- Rewards/margins: 0.0551
- Logps/rejected: -0.6233
- Logps/chosen: -0.0722
- Logits/rejected: -0.4048
- Logits/chosen: -0.3432
- Sft Loss: 0.0119
- Odds Ratio Loss: 0.8243
## 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | Odds Ratio Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 1.3352 | 1.4815 | 50 | 1.0317 | -0.0989 | -0.1576 | 0.8333 | 0.0587 | -1.5758 | -0.9889 | -0.4812 | -0.4002 | 0.1167 | 9.1492 |
| 0.2371 | 2.9630 | 100 | 0.1655 | -0.0135 | -0.0699 | 0.8833 | 0.0564 | -0.6987 | -0.1348 | -0.4551 | -0.3813 | 0.0177 | 1.4782 |
| 0.1421 | 4.4444 | 150 | 0.1010 | -0.0077 | -0.0577 | 0.8833 | 0.0500 | -0.5773 | -0.0770 | -0.4107 | -0.3473 | 0.0124 | 0.8869 |
| 0.1291 | 5.9259 | 200 | 0.0984 | -0.0075 | -0.0594 | 0.8833 | 0.0518 | -0.5936 | -0.0752 | -0.4066 | -0.3442 | 0.0123 | 0.8613 |
| 0.1246 | 7.4074 | 250 | 0.0943 | -0.0072 | -0.0623 | 0.8833 | 0.0551 | -0.6233 | -0.0722 | -0.4048 | -0.3432 | 0.0119 | 0.8243 |
| 0.1045 | 8.8889 | 300 | 0.0948 | -0.0072 | -0.0628 | 0.8833 | 0.0555 | -0.6277 | -0.0724 | -0.4046 | -0.3432 | 0.0119 | 0.8292 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.45.2
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.20.0 |