safetensors generated_from_trainer base_model:meta-llama/Llama-2-7b-hf region:us
---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama2-7b-dpo-lora-20231129-32
  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. -->

# llama2-7b-dpo-lora-20231129-32

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6869
- Rewards/chosen: 0.0290
- Rewards/rejected: 0.0096
- Rewards/accuracies: 0.5833
- Rewards/margins: 0.0193
- Logps/rejected: -288.6959
- Logps/chosen: -359.9739
- Logits/rejected: -0.3197
- Logits/chosen: -0.1734

## 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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6918        | 1.0   | 121  | 0.6911          | 0.0118         | 0.0027           | 0.5159             | 0.0091          | -288.7652      | -360.1456    | -0.3204         | -0.1740       |
| 0.6887        | 2.0   | 242  | 0.6886          | 0.0182         | 0.0065           | 0.5437             | 0.0118          | -288.7276      | -360.0812    | -0.3203         | -0.1741       |
| 0.6865        | 3.0   | 363  | 0.6869          | 0.0290         | 0.0096           | 0.5833             | 0.0193          | -288.6959      | -359.9739    | -0.3197         | -0.1734       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
