---
license: mit
base_model: HuggingFaceH4/mistral-7b-sft-beta
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 is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistral-7b-sft-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0465
- Rewards/chosen: -2.6400
- Rewards/rejected: -3.4900
- Rewards/accuracies: 0.7227
- Rewards/margins: 0.8499
- Logps/rejected: -606.3505
- Logps/chosen: -521.0439
- Logits/rejected: -1.9091
- Logits/chosen: -1.9501

## 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: 5
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1485        | 0.11  | 100  | 0.1803          | -0.5621        | -0.7737          | 0.6406             | 0.2117          | -334.7263      | -313.2471    | -2.4998         | -2.5133       |
| 0.0592        | 0.23  | 200  | 0.0662          | -1.7402        | -2.3280          | 0.6797             | 0.5878          | -490.1518      | -431.0574    | -2.2396         | -2.2729       |
| 0.0394        | 0.34  | 300  | 0.0494          | -2.3707        | -2.9767          | 0.6953             | 0.6061          | -555.0248      | -494.1047    | -2.1101         | -2.1389       |
| 0.0401        | 0.45  | 400  | 0.0523          | -2.4275        | -3.1076          | 0.7031             | 0.6801          | -568.1116      | -499.7916    | -2.0429         | -2.0799       |
| 0.0335        | 0.57  | 500  | 0.0461          | -2.4063        | -3.2276          | 0.7148             | 0.8213          | -580.1129      | -497.6727    | -2.0057         | -2.0456       |
| 0.0273        | 0.68  | 600  | 0.0409          | -2.8465        | -3.7152          | 0.7070             | 0.8687          | -628.8741      | -541.6862    | -1.9162         | -1.9558       |
| 0.0377        | 0.79  | 700  | 0.0496          | -2.5317        | -3.3682          | 0.7227             | 0.8365          | -594.1712      | -510.2102    | -1.9274         | -1.9673       |
| 0.0352        | 0.91  | 800  | 0.0465          | -2.6400        | -3.4900          | 0.7227             | 0.8499          | -606.3505      | -521.0439    | -1.9091         | -1.9501       |


### Framework versions

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