---
library_name: transformers
license: gemma
base_model: unsloth/gemma-2-9b-it
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- sam-paech/gutenbergs_1_2_3_antislop-dpo
model-index:
- name: gemma-2-9b-it-gutenberg3
  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-2-9b-it-gutenberg3

This model is a fine-tuned version of [unsloth/gemma-2-9b-it](https://huggingface.co/unsloth/gemma-2-9b-it) on the sam-paech/gutenbergs_1_2_3_antislop-dpo dataset.
It achieves the following results on the evaluation set:
- Loss: 6.3949
- Rewards/chosen: -23.4522
- Rewards/rejected: -23.5795
- Rewards/accuracies: 0.5
- Rewards/margins: 0.1273
- Logps/rejected: -2.3579
- Logps/chosen: -2.3452

## 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: 1e-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- 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: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|
| 5.5632        | 0.6932 | 400  | 6.3949          | -23.4522       | -23.5795         | 0.5                | 0.1273          | -2.3579        | -2.3452      |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.2.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1