---
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: dpo-selective-mixdata
  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. -->

# dpo-selective-mixdata

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5805
- Rewards/chosen: -4.7292
- Rewards/rejected: -5.2763
- Rewards/accuracies: 0.6934
- Rewards/margins: 0.5471
- Logps/rejected: -654.5243
- Logps/chosen: -590.7578
- Logits/rejected: 6.2956
- Logits/chosen: 6.4467

## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5481        | 0.27  | 500  | 0.6089          | -2.6822        | -3.1236          | 0.6705             | 0.4414          | -439.2521      | -386.0565    | 3.9671          | 4.1604        |
| 0.5519        | 0.53  | 1000 | 0.5867          | -4.2523        | -4.7597          | 0.6894             | 0.5074          | -602.8671      | -543.0739    | 5.1974          | 5.3486        |
| 0.5597        | 0.8   | 1500 | 0.5821          | -4.7906        | -5.3218          | 0.6959             | 0.5311          | -659.0733      | -596.9037    | 6.4644          | 6.6294        |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.0