---
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full
  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-full

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5261
- Rewards/chosen: -2.4591
- Rewards/rejected: -3.9221
- Rewards/accuracies: 0.7773
- Rewards/margins: 1.4631
- Logps/rejected: -703.8400
- Logps/chosen: -549.4910
- Logits/rejected: 0.0289
- Logits/chosen: 0.0663

## 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: 1e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 2
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6201        | 0.21  | 100  | 0.6253          | -0.2753        | -0.6662          | 0.7031             | 0.3909          | -378.2405      | -331.1124    | 0.4172          | 0.3706        |
| 0.5547        | 0.42  | 200  | 0.5549          | -0.6988        | -1.4726          | 0.7656             | 0.7738          | -458.8863      | -373.4661    | 0.4261          | 0.3909        |
| 0.5343        | 0.63  | 300  | 0.5316          | -0.8044        | -1.6474          | 0.7656             | 0.8430          | -476.3628      | -384.0199    | 0.2851          | 0.2449        |
| 0.5323        | 0.84  | 400  | 0.5211          | -0.9068        | -1.8283          | 0.7812             | 0.9216          | -494.4600      | -394.2621    | 0.2834          | 0.2514        |
| 0.352         | 1.05  | 500  | 0.5258          | -1.9533        | -3.4166          | 0.7969             | 1.4634          | -653.2899      | -498.9117    | -0.0846         | -0.0654       |
| 0.3342        | 1.26  | 600  | 0.5268          | -2.3123        | -3.7246          | 0.7930             | 1.4124          | -684.0857      | -534.8101    | 0.1128          | 0.1344        |
| 0.337         | 1.47  | 700  | 0.5290          | -2.3753        | -3.8837          | 0.7773             | 1.5084          | -699.9910      | -541.1116    | 0.0099          | 0.0414        |
| 0.3398        | 1.67  | 800  | 0.5297          | -2.5097        | -4.0133          | 0.7734             | 1.5036          | -712.9506      | -554.5546    | 0.0381          | 0.0750        |
| 0.307         | 1.88  | 900  | 0.5261          | -2.4591        | -3.9221          | 0.7773             | 1.4631          | -703.8400      | -549.4910    | 0.0289          | 0.0663        |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1