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-20231129-52
  results: []
---

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# llama2-7b-dpo-lora-20231129-52

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: 0.0289
- Rewards/rejected: 0.0137
- Rewards/accuracies: 0.5675
- Rewards/margins: 0.0152
- Logps/rejected: -288.6960
- Logps/chosen: -359.9693
- Logits/rejected: -0.3198
- Logits/chosen: -0.1736

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6911        | 1.0   | 121  | 0.6918          | 0.0084         | 0.0083           | 0.5238             | 0.0001          | -288.7494      | -360.1742    | -0.3206         | -0.1740       |
| 0.6892        | 2.0   | 242  | 0.6888          | 0.0170         | 0.0139           | 0.4841             | 0.0032          | -288.6942      | -360.0880    | -0.3202         | -0.1740       |
| 0.6867        | 3.0   | 363  | 0.6869          | 0.0289         | 0.0137           | 0.5675             | 0.0152          | -288.6960      | -359.9693    | -0.3198         | -0.1736       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.1
- Datasets 2.14.6
- Tokenizers 0.14.1
