---
license: apache-2.0
base_model: NousResearch/Yarn-Mistral-7b-128k
tags:
- generated_from_trainer
model-index:
- name: unraveled-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. -->

# unraveled-7b-dpo-lora

This model is a fine-tuned version of [NousResearch/Yarn-Mistral-7b-128k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k), following the Zephyr alignment protocol.
It achieves the following results on the evaluation set:
- Loss: 0.5895
- Rewards/chosen: 0.1439
- Rewards/rejected: -0.1833
- Rewards/accuracies: 0.6880
- Rewards/margins: 0.3272
- Logps/rejected: -221.8329
- Logps/chosen: -266.1414
- Logits/rejected: -1.9675
- Logits/chosen: -2.0859

## 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: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- total_eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6313        | 1.0   | 242  | 0.6318          | 0.1228         | -0.0304          | 0.6600             | 0.1532          | -220.3036      | -266.3521    | -1.9863         | -2.1062       |
| 0.6013        | 2.0   | 484  | 0.5983          | 0.1484         | -0.1334          | 0.6760             | 0.2819          | -221.3338      | -266.0959    | -1.9723         | -2.0914       |
| 0.5889        | 3.0   | 726  | 0.5895          | 0.1439         | -0.1833          | 0.6880             | 0.3272          | -221.8329      | -266.1414    | -1.9675         | -2.0859       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1