---
library_name: transformers
license: gemma
base_model: google/gemma-7b
tags:
- alignment-handbook
- trl
- orpo
- generated_from_trainer
- trl
- orpo
- generated_from_trainer
datasets:
- silviasapora/low_quality_dpo7k
model-index:
- name: gemma-7b-borpo-low-quality-v3
  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-7b-borpo-low-quality-v3

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the silviasapora/low_quality_dpo7k dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1095
- Rewards/chosen: -0.6954
- Rewards/rejected: -0.8346
- Rewards/accuracies: 0.5571
- Rewards/margins: 0.1392
- Logps/rejected: -1.6692
- Logps/chosen: -1.3909
- Logits/rejected: 262.5518
- Logits/chosen: 319.3429
- Nll Loss: 1.7836
- Log Odds Ratio: -0.6395
- Log Odds Chosen: 0.4455

## 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-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.9721        | 1.0   | 168  | 1.9526          | -0.6072        | -0.7027          | 0.5571             | 0.0955          | -1.4054        | -1.2144      | 282.1215        | 336.2867      | 1.6515   | -0.6573        | 0.2649          |
| 1.3299        | 2.0   | 336  | 1.9015          | -0.5986        | -0.6805          | 0.5                | 0.0820          | -1.3611        | -1.1972      | 293.2820        | 345.2333      | 1.5933   | -0.6792        | 0.2173          |
| 0.6266        | 3.0   | 504  | 2.1095          | -0.6954        | -0.8346          | 0.5571             | 0.1392          | -1.6692        | -1.3909      | 262.5518        | 319.3429      | 1.7836   | -0.6395        | 0.4455          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1