---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- sablo/HelpSteer_binarized
base_model: sablo/sablo-pebble-mistral
model-index:
- name: sablo-pebble-mistral-dpo-lora-HelpSteer_binarized
  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. -->

# sablo-pebble-mistral-dpo-lora-HelpSteer_binarized

This model is a fine-tuned version of [sablo/sablo-pebble-mistral](https://huggingface.co/sablo/sablo-pebble-mistral) on the sablo/HelpSteer_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5371
- Rewards/chosen: -0.9335
- Rewards/rejected: -1.6455
- Rewards/accuracies: 0.7264
- Rewards/margins: 0.7121
- Logps/rejected: -298.0735
- Logps/chosen: -253.4149
- Logits/rejected: -2.4554
- Logits/chosen: -2.5093

## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6874        | 0.1   | 100  | 0.6892          | 0.0213         | 0.0133           | 0.6698             | 0.0080          | -132.1924      | -157.9395    | -2.4463         | -2.4843       |
| 0.6592        | 0.2   | 200  | 0.6594          | 0.0055         | -0.0704          | 0.6698             | 0.0759          | -140.5588      | -159.5180    | -2.4922         | -2.5370       |
| 0.5451        | 0.3   | 300  | 0.5867          | -0.4490        | -0.7587          | 0.6863             | 0.3097          | -209.3938      | -204.9713    | -2.5128         | -2.5620       |
| 0.4933        | 0.39  | 400  | 0.5591          | -0.6060        | -1.1029          | 0.7146             | 0.4968          | -243.8062      | -220.6713    | -2.4868         | -2.5386       |
| 0.5271        | 0.49  | 500  | 0.5488          | -0.6712        | -1.2738          | 0.7193             | 0.6026          | -260.8958      | -227.1889    | -2.4784         | -2.5312       |
| 0.4594        | 0.59  | 600  | 0.5418          | -0.7977        | -1.4672          | 0.7311             | 0.6695          | -280.2420      | -239.8430    | -2.4672         | -2.5200       |
| 0.5444        | 0.69  | 700  | 0.5358          | -0.7688        | -1.4528          | 0.7335             | 0.6840          | -278.8014      | -236.9531    | -2.4594         | -2.5127       |
| 0.5755        | 0.79  | 800  | 0.5405          | -1.0672        | -1.7631          | 0.7311             | 0.6959          | -309.8293      | -266.7906    | -2.4585         | -2.5118       |
| 0.5495        | 0.89  | 900  | 0.5371          | -0.9321        | -1.6450          | 0.7288             | 0.7129          | -298.0242      | -253.2804    | -2.4558         | -2.5096       |
| 0.5948        | 0.98  | 1000 | 0.5371          | -0.9335        | -1.6455          | 0.7264             | 0.7121          | -298.0735      | -253.4149    | -2.4554         | -2.5093       |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.15.0