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---
library_name: peft
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct_dpo_sg_values_p025_OA_gold
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_dpo_sg_values_p025_OA_gold
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 dpo_sg_values_p025_OA_gold dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1369
- Rewards/chosen: -0.3243
- Rewards/rejected: -3.7445
- Rewards/accuracies: 0.9400
- Rewards/margins: 3.4202
- Logps/chosen: -5.3343
- Logps/rejected: -44.0676
- Logits/chosen: -0.8235
- Logits/rejected: -0.8529
## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:|
| 0.677 | 0.1495 | 250 | 0.6611 | -0.0030 | -0.0688 | 0.8780 | 0.0658 | -2.1210 | -7.3104 | -0.6673 | -0.6792 |
| 0.4141 | 0.2990 | 500 | 0.3328 | -0.1370 | -1.2934 | 0.8960 | 1.1564 | -3.4617 | -19.5564 | -0.7405 | -0.7604 |
| 0.1869 | 0.4486 | 750 | 0.1943 | -0.3266 | -2.7983 | 0.9280 | 2.4718 | -5.3572 | -34.6058 | -0.8272 | -0.8525 |
| 0.1234 | 0.5981 | 1000 | 0.1579 | -0.3430 | -3.2984 | 0.9380 | 2.9554 | -5.5213 | -39.6065 | -0.8336 | -0.8610 |
| 0.122 | 0.7476 | 1250 | 0.1439 | -0.3187 | -3.5609 | 0.9360 | 3.2422 | -5.2784 | -42.2310 | -0.8265 | -0.8553 |
| 0.0821 | 0.8971 | 1500 | 0.1398 | -0.3263 | -3.7101 | 0.9340 | 3.3838 | -5.3544 | -43.7234 | -0.8241 | -0.8535 |
### Framework versions
- PEFT 0.15.2
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 2.21.0
- Tokenizers 0.21.1 |