---
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: llama3-8b-base-dpo-120
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhaoyang1/huggingface/runs/fbpwm86a)
# llama3-8b-base-dpo-120

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4893
- Rewards/chosen: -0.5883
- Rewards/rejected: -1.3409
- Rewards/accuracies: 0.6905
- Rewards/margins: 0.7525
- Logps/rejected: -293.5897
- Logps/chosen: -331.5697
- Logits/rejected: 0.4485
- Logits/chosen: 0.2338

## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 24
- gradient_accumulation_steps: 5
- total_train_batch_size: 120
- total_eval_batch_size: 48
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.467         | 0.4906 | 250  | 0.4987          | -0.6034        | -1.2547          | 0.7262             | 0.6512          | -291.8655      | -331.8713    | 0.4838          | 0.2542        |
| 0.4536        | 0.9812 | 500  | 0.4893          | -0.5883        | -1.3409          | 0.6905             | 0.7525          | -293.5897      | -331.5697    | 0.4485          | 0.2338        |


### Framework versions

- Transformers 4.42.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1