---
base_model: allenai/tulu-2-7b
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-lora
  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. -->

# zephyr-7b-dpo-lora

This model is a fine-tuned version of [allenai/tulu-2-7b](https://huggingface.co/allenai/tulu-2-7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6551
- Rewards/chosen: -0.0635
- Rewards/rejected: -0.1612
- Rewards/accuracies: 0.6905
- Rewards/margins: 0.0978
- Logps/rejected: -241.7965
- Logps/chosen: -271.5237
- Logits/rejected: -1.4412
- Logits/chosen: -1.2746

## 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: 6
- gradient_accumulation_steps: 8
- total_train_batch_size: 96
- total_eval_batch_size: 24
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6812        | 1.0   | 645  | 0.6832          | -0.0153        | -0.0425          | 0.6190             | 0.0271          | -240.6086      | -271.0424    | -1.4556         | -1.2853       |
| 0.667         | 2.0   | 1291 | 0.6636          | -0.0473        | -0.1169          | 0.6518             | 0.0695          | -241.3527      | -271.3625    | -1.4457         | -1.2786       |
| 0.6518        | 3.0   | 1935 | 0.6551          | -0.0635        | -0.1612          | 0.6905             | 0.0978          | -241.7965      | -271.5237    | -1.4412         | -1.2746       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1