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---
base_model: princeton-nlp/Llama-3-Base-8B-SFT
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: llama3-dpo-lora
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. -->
# llama3-dpo-lora
This model is a fine-tuned version of [princeton-nlp/Llama-3-Base-8B-SFT](https://huggingface.co/princeton-nlp/Llama-3-Base-8B-SFT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5193
- Rewards/chosen: 0.0154
- Rewards/rejected: -0.7979
- Rewards/accuracies: 0.7280
- Rewards/margins: 0.8133
- Logps/rejected: -284.6558
- Logps/chosen: -292.3936
- Logits/rejected: -0.3843
- Logits/chosen: -0.4157
## 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: 1
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6275 | 0.1047 | 100 | 0.6122 | 0.2594 | -0.0099 | 0.6920 | 0.2693 | -276.7753 | -289.9533 | -0.5582 | -0.5619 |
| 0.5726 | 0.2094 | 200 | 0.5529 | -0.0787 | -0.6353 | 0.7040 | 0.5565 | -283.0293 | -293.3344 | -0.5103 | -0.5266 |
| 0.5429 | 0.3141 | 300 | 0.5380 | -0.1730 | -0.8455 | 0.7260 | 0.6725 | -285.1317 | -294.2773 | -0.4689 | -0.4910 |
| 0.5054 | 0.4187 | 400 | 0.5332 | -0.0870 | -0.8469 | 0.7240 | 0.7599 | -285.1459 | -293.4173 | -0.4261 | -0.4535 |
| 0.5508 | 0.5234 | 500 | 0.5267 | -0.0207 | -0.8088 | 0.7180 | 0.7881 | -284.7646 | -292.7540 | -0.4045 | -0.4335 |
| 0.5338 | 0.6281 | 600 | 0.5263 | 0.1981 | -0.5901 | 0.7300 | 0.7882 | -282.5771 | -290.5659 | -0.4002 | -0.4304 |
| 0.5064 | 0.7328 | 700 | 0.5175 | -0.2007 | -1.0076 | 0.7300 | 0.8068 | -286.7521 | -294.5546 | -0.3761 | -0.4080 |
| 0.5349 | 0.8375 | 800 | 0.5197 | 0.0149 | -0.7896 | 0.7200 | 0.8045 | -284.5727 | -292.3984 | -0.3853 | -0.4161 |
| 0.4775 | 0.9422 | 900 | 0.5181 | 0.0150 | -0.7988 | 0.7260 | 0.8139 | -284.6649 | -292.3968 | -0.3842 | -0.4151 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.44.2
- Pytorch 2.2.1+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1 |