---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: llama2-13b-dpo-lora-20231205-32
  results: []
---

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# llama2-13b-dpo-lora-20231205-32

This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6891
- Rewards/chosen: 0.0224
- Rewards/rejected: 0.0145
- Rewards/accuracies: 0.5675
- Rewards/margins: 0.0079
- Logps/rejected: -245.1621
- Logps/chosen: -309.3195
- Logits/rejected: -1.2044
- Logits/chosen: -1.4437

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.691         | 1.0   | 121  | 0.6911          | 0.0078         | 0.0020           | 0.5040             | 0.0058          | -245.2879      | -309.4661    | -1.2040         | -1.4432       |
| 0.6895        | 2.0   | 242  | 0.6903          | 0.0202         | 0.0107           | 0.5317             | 0.0095          | -245.2007      | -309.3419    | -1.2045         | -1.4435       |
| 0.6889        | 3.0   | 363  | 0.6891          | 0.0224         | 0.0145           | 0.5675             | 0.0079          | -245.1621      | -309.3195    | -1.2044         | -1.4437       |


### Framework versions

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