---
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: 0.3183
- Rewards/chosen: -0.6032
- Rewards/rejected: -2.1160
- Rewards/accuracies: 0.8711
- Rewards/margins: 1.5128
- Logps/rejected: -584.2130
- Logps/chosen: -439.6992
- Logits/rejected: -5.8852
- Logits/chosen: -5.4031

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5118        | 0.1151 | 100  | 0.5923          | -0.1120        | -0.4506          | 0.7070             | 0.3386          | -417.6701      | -390.5766    | -2.1984         | -2.2213       |
| 0.4206        | 0.2303 | 200  | 0.5055          | -0.2913        | -1.0785          | 0.8008             | 0.7872          | -480.4641      | -408.5089    | -3.2280         | -3.1644       |
| 0.4144        | 0.3454 | 300  | 0.4504          | -0.3084        | -1.2736          | 0.7773             | 0.9651          | -499.9700      | -410.2218    | -4.0963         | -3.8861       |
| 0.4011        | 0.4606 | 400  | 0.4135          | -0.4247        | -1.5332          | 0.8086             | 1.1086          | -525.9362      | -421.8441    | -4.8370         | -4.5018       |
| 0.3915        | 0.5757 | 500  | 0.3740          | -0.3892        | -1.7143          | 0.8516             | 1.3251          | -544.0394      | -418.2938    | -5.1877         | -4.7675       |
| 0.3726        | 0.6908 | 600  | 0.3468          | -0.4807        | -1.8892          | 0.8438             | 1.4085          | -561.5286      | -427.4439    | -5.6248         | -5.1461       |
| 0.3522        | 0.8060 | 700  | 0.3249          | -0.5431        | -2.0476          | 0.8789             | 1.5044          | -577.3692      | -433.6906    | -5.6819         | -5.2107       |
| 0.3643        | 0.9211 | 800  | 0.3183          | -0.6032        | -2.1160          | 0.8711             | 1.5128          | -584.2130      | -439.6992    | -5.8852         | -5.4031       |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.19.1