---
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: 0.4920
- Rewards/chosen: -2.3074
- Rewards/rejected: -3.5196
- Rewards/accuracies: 0.7734
- Rewards/margins: 1.2122
- Logps/rejected: -609.3139
- Logps/chosen: -487.7755
- Logits/rejected: -0.7242
- Logits/chosen: -0.9597

## 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: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5392        | 0.11  | 100  | 0.6286          | -0.6554        | -0.9418          | 0.6523             | 0.2865          | -351.5352      | -322.5750    | -2.5756         | -2.5908       |
| 0.4524        | 0.23  | 200  | 0.5475          | -1.4831        | -2.1698          | 0.7227             | 0.6867          | -474.3327      | -405.3454    | -1.9678         | -1.9878       |
| 0.3976        | 0.34  | 300  | 0.5194          | -1.8541        | -2.8790          | 0.7617             | 1.0249          | -545.2501      | -442.4474    | -0.9783         | -1.1841       |
| 0.3892        | 0.45  | 400  | 0.5160          | -2.0795        | -3.1766          | 0.7773             | 1.0971          | -575.0087      | -464.9888    | -0.6002         | -0.8579       |
| 0.3964        | 0.57  | 500  | 0.4992          | -2.1896        | -3.3081          | 0.7656             | 1.1185          | -588.1666      | -476.0038    | -0.8012         | -1.0189       |
| 0.4149        | 0.68  | 600  | 0.4948          | -2.2061        | -3.3241          | 0.7461             | 1.1179          | -589.7601      | -477.6525    | -1.0527         | -1.2398       |
| 0.4004        | 0.79  | 700  | 0.4905          | -2.1723        | -3.3652          | 0.7695             | 1.1929          | -593.8731      | -474.2662    | -0.8519         | -1.0643       |
| 0.3887        | 0.91  | 800  | 0.4920          | -2.3074        | -3.5196          | 0.7734             | 1.2122          | -609.3139      | -487.7755    | -0.7242         | -0.9597       |


### Framework versions

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