---
base_model: meta-llama/Llama-2-7b-hf
library_name: peft
license: llama2
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama-2-7b-hf-DPO-LookAhead-0_TTree1.4_TT0.9_TP0.7_TE0.2_V3
  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. -->

# Llama-2-7b-hf-DPO-LookAhead-0_TTree1.4_TT0.9_TP0.7_TE0.2_V3

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: 0.7312
- Rewards/chosen: -2.2500
- Rewards/rejected: -3.0688
- Rewards/accuracies: 0.6667
- Rewards/margins: 0.8189
- Logps/rejected: -156.0040
- Logps/chosen: -95.9953
- Logits/rejected: 0.0075
- Logits/chosen: 0.0375

## 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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6606        | 0.3035 | 78   | 0.6743          | 0.0166         | -0.0081          | 0.75               | 0.0247          | -125.3963      | -73.3299     | 0.5935          | 0.6202        |
| 0.5493        | 0.6070 | 156  | 0.6634          | -0.1831        | -0.2415          | 0.6667             | 0.0585          | -127.7309      | -75.3266     | 0.5586          | 0.5847        |
| 0.5705        | 0.9105 | 234  | 0.5848          | -0.3315        | -0.6168          | 0.6667             | 0.2853          | -131.4834      | -76.8105     | 0.4949          | 0.5208        |
| 0.405         | 1.2140 | 312  | 0.5806          | -0.8206        | -1.3076          | 0.5833             | 0.4870          | -138.3913      | -81.7017     | 0.4210          | 0.4471        |
| 0.5029        | 1.5175 | 390  | 0.5738          | -1.0140        | -1.5365          | 0.6667             | 0.5225          | -140.6803      | -83.6359     | 0.3256          | 0.3525        |
| 0.1719        | 1.8210 | 468  | 0.6151          | -1.3642        | -1.9154          | 0.75               | 0.5512          | -144.4694      | -87.1375     | 0.1929          | 0.2203        |
| 0.3565        | 2.1245 | 546  | 0.6575          | -1.6573        | -2.3806          | 0.75               | 0.7233          | -149.1218      | -90.0692     | 0.1075          | 0.1363        |
| 0.4206        | 2.4280 | 624  | 0.7578          | -2.2884        | -3.1134          | 0.6667             | 0.8250          | -156.4492      | -96.3796     | 0.0126          | 0.0427        |
| 0.3123        | 2.7315 | 702  | 0.7312          | -2.2500        | -3.0688          | 0.6667             | 0.8189          | -156.0040      | -95.9953     | 0.0075          | 0.0375        |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1