---
license: other
base_model: HuggingFaceH4/zephyr-7b-gemma-sft-v0.1
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- argilla/dpo-mix-7k
model-index:
- name: gemma_rpo_eta0.005_no_decay
  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. -->

# gemma_rdpo_eta0.005_no_decay

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: 0.5899
- Rewards/chosen: -0.7561
- Rewards/rejected: -2.1676
- Rewards/accuracies: 0.7234
- Rewards/margins: 1.4115
- Logps/rejected: -464.4193
- Logps/chosen: -408.9966
- Logits/rejected: 161.6372
- Logits/chosen: 163.3166
- Eta: 0.0050

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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 | Eta    |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:------:|
| 0.5915        | 0.9479 | 50   | 0.5745          | -0.7212        | -1.8546          | 0.7021             | 1.1334          | -458.1599      | -408.3000    | 171.6370        | 174.0368      | 0.0050 |
| 0.2599        | 1.8957 | 100  | 0.5899          | -0.7561        | -2.1676          | 0.7234             | 1.4115          | -464.4193      | -408.9966    | 161.6372        | 163.3166      | 0.0050 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1