---
library_name: transformers
base_model: princeton-nlp/Llama-3-Base-8B-SFT
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: Llama-3-dpo-5e-7-SFTed-paged_adamw_32bit-1.0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-3-dpo-5e-7-SFTed-paged_adamw_32bit-1.0

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 HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5487
- Rewards/chosen: -1.1436
- Rewards/rejected: -1.6789
- Rewards/accuracies: 0.7380
- Rewards/margins: 0.5353
- Logps/rejected: -435.4569
- Logps/chosen: -405.1720
- Logits/rejected: -0.7446
- Logits/chosen: -0.7091

## 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-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6829        | 0.1047 | 50   | 0.6802          | 0.0612         | 0.0336           | 0.6580             | 0.0276          | -264.2072      | -284.6938    | -0.7278         | -0.6508       |
| 0.6237        | 0.2094 | 100  | 0.6211          | -0.1187        | -0.3023          | 0.7080             | 0.1836          | -297.7958      | -302.6812    | -0.7410         | -0.6815       |
| 0.5943        | 0.3141 | 150  | 0.5984          | -0.2406        | -0.5058          | 0.6980             | 0.2653          | -318.1529      | -314.8689    | -0.7015         | -0.6515       |
| 0.5788        | 0.4187 | 200  | 0.5731          | -0.6524        | -1.0298          | 0.7100             | 0.3774          | -370.5502      | -356.0472    | -0.7012         | -0.6568       |
| 0.5518        | 0.5234 | 250  | 0.5652          | -1.0017        | -1.4643          | 0.7260             | 0.4627          | -414.0016      | -390.9777    | -0.7286         | -0.6885       |
| 0.5472        | 0.6281 | 300  | 0.5599          | -1.0502        | -1.5173          | 0.7220             | 0.4671          | -419.2986      | -395.8287    | -0.7269         | -0.6862       |
| 0.5215        | 0.7328 | 350  | 0.5506          | -1.0201        | -1.5402          | 0.7380             | 0.5201          | -421.5936      | -392.8219    | -0.7402         | -0.7031       |
| 0.5415        | 0.8375 | 400  | 0.5494          | -1.1153        | -1.6479          | 0.7460             | 0.5326          | -432.3640      | -402.3448    | -0.7419         | -0.7055       |
| 0.5368        | 0.9422 | 450  | 0.5487          | -1.1436        | -1.6789          | 0.7380             | 0.5353          | -435.4569      | -405.1720    | -0.7446         | -0.7091       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1

arxiv.org/abs/2502.07599