---
license: other
base_model: HuggingFaceH4/zephyr-7b-gemma-sft-v0.1
tags:
- choo-choo
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- choo-choo
- generated_from_trainer
model-index:
- name: zephyr-gemma-dpo-faithful
  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-gemma-dpo-faithful

This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-gemma-sft-v0.1](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-sft-v0.1) on the argilla/dpo-mix-7k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4498
- Rewards/chosen: -1.7969
- Rewards/rejected: -3.5156
- Rewards/accuracies: 0.7394
- Rewards/margins: 1.7188
- Logps/rejected: -476.0
- Logps/chosen: -388.0
- Logits/rejected: 89.5
- Logits/chosen: 87.0

## 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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 100
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5155        | 0.95  | 100  | 0.5003          | -1.2422        | -2.5156          | 0.6862             | 1.2656          | -456.0         | -378.0       | 97.5            | 95.0          |
| 0.1902        | 1.9   | 200  | 0.4498          | -1.7969        | -3.5156          | 0.7394             | 1.7188          | -476.0         | -388.0       | 89.5            | 87.0          |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2