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---
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- trl
- dpo
- generated_from_trainer
library_name: peft
model-index:
- name: Llama-2-7b-hf-DPO-LookAhead-5_TTree1.4_TT0.9_TP0.7_TE0.2_V6
  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-5_TTree1.4_TT0.9_TP0.7_TE0.2_V6

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: 1.0184
- Rewards/chosen: -1.6627
- Rewards/rejected: -1.4611
- Rewards/accuracies: 0.5
- Rewards/margins: -0.2016
- Logps/rejected: -142.2372
- Logps/chosen: -159.6465
- Logits/rejected: -0.2970
- Logits/chosen: -0.3265

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6746        | 0.3012 | 75   | 0.6658          | 0.0862         | 0.0321           | 0.75               | 0.0541          | -127.3055      | -142.1577    | 0.1821          | 0.1663        |
| 0.5925        | 0.6024 | 150  | 0.6506          | 0.1218         | 0.0304           | 0.5833             | 0.0914          | -127.3224      | -141.8020    | 0.1565          | 0.1401        |
| 0.7335        | 0.9036 | 225  | 0.7279          | -0.0626        | -0.0395          | 0.5                | -0.0231         | -128.0216      | -143.6459    | 0.1275          | 0.1103        |
| 0.6498        | 1.2048 | 300  | 0.7880          | -0.2917        | -0.2254          | 0.4167             | -0.0663         | -129.8807      | -145.9371    | 0.0678          | 0.0485        |
| 0.386         | 1.5060 | 375  | 0.7303          | -0.2014        | -0.2339          | 0.5                | 0.0325          | -129.9658      | -145.0339    | 0.0325          | 0.0140        |
| 0.2307        | 1.8072 | 450  | 0.8159          | -0.5206        | -0.4793          | 0.5                | -0.0412         | -132.4201      | -148.2257    | -0.0582         | -0.0797       |
| 0.1034        | 2.1084 | 525  | 0.9133          | -1.0254        | -0.8918          | 0.4167             | -0.1335         | -136.5451      | -153.2736    | -0.2025         | -0.2290       |
| 0.284         | 2.4096 | 600  | 1.0153          | -1.5972        | -1.3870          | 0.4167             | -0.2102         | -141.4962      | -158.9917    | -0.2790         | -0.3083       |
| 0.0599        | 2.7108 | 675  | 1.0184          | -1.6627        | -1.4611          | 0.5                | -0.2016         | -142.2372      | -159.6465    | -0.2970         | -0.3265       |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1