---
license: gemma
base_model: google/gemma-7b
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- argilla/dpo-mix-7k
model-index:
- name: zephyr-7b-gemma-dpo
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://zebra.wandb.io/cto/distillm/runs/n5v6nn5w)
# zephyr-7b-gemma-dpo

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the argilla/dpo-mix-7k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8036
- Rewards/chosen: -0.4463
- Rewards/rejected: -1.2861
- Rewards/accuracies: 0.7292
- Rewards/margins: 0.8397
- Logps/rejected: -1648.0323
- Logps/chosen: -1530.0571
- Logits/rejected: -25.1620
- Logits/chosen: -18.0449

## 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: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4114        | 1.8957 | 100  | 0.8002          | -0.4660        | -1.3128          | 0.7604             | 0.8468          | -1648.5675     | -1530.4515   | -25.1625        | -18.0007      |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1