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---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
- tanliboy/orca_dpo_pairs
model-index:
- name: lambda-llama-3-8b-dpo-test-orca
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. -->
# lambda-llama-3-8b-dpo-test-orca
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the HuggingFaceH4/ultrafeedback_binarized and the tanliboy/orca_dpo_pairs datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4795
- Rewards/chosen: -1.6860
- Rewards/rejected: -2.8132
- Rewards/accuracies: 0.7259
- Rewards/margins: 1.1272
- Logps/rejected: -645.5051
- Logps/chosen: -549.3651
- Logits/rejected: -2.6630
- Logits/chosen: -2.5985
## 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: 2e-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6011 | 0.1744 | 100 | 0.5738 | -0.8770 | -1.2808 | 0.6988 | 0.4038 | -492.2603 | -468.4565 | -2.4544 | -2.4042 |
| 0.5447 | 0.3489 | 200 | 0.5242 | -1.3236 | -2.0879 | 0.7289 | 0.7644 | -572.9752 | -513.1177 | -2.6319 | -2.5732 |
| 0.5173 | 0.5233 | 300 | 0.5003 | -1.6828 | -2.6810 | 0.7259 | 0.9982 | -632.2809 | -549.0404 | -2.6140 | -2.5556 |
| 0.5144 | 0.6978 | 400 | 0.4851 | -1.7107 | -2.8135 | 0.7319 | 1.1028 | -645.5279 | -551.8306 | -2.7027 | -2.6365 |
| 0.5162 | 0.8722 | 500 | 0.4798 | -1.7085 | -2.8440 | 0.7259 | 1.1355 | -648.5815 | -551.6072 | -2.6442 | -2.5812 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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