---
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-v5
  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-v5

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: 2.0035
- Rewards/chosen: -0.6455
- Rewards/rejected: -0.7620
- Rewards/accuracies: 0.6115
- Rewards/margins: 0.1164
- Logps/rejected: -1.5240
- Logps/chosen: -1.2911
- Logits/rejected: 259.2041
- Logits/chosen: 292.7468
- Nll Loss: 1.6440
- Log Odds Ratio: -0.6769
- Log Odds Chosen: 0.3357

## 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: 7.5e-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.8398        | 0.9955 | 167  | 1.8982          | -0.5762        | -0.6715          | 0.5180             | 0.0953          | -1.3431        | -1.1525      | 302.9095        | 331.1552      | 1.5454   | -0.6749        | 0.2542          |
| 1.299         | 1.9970 | 335  | 1.8186          | -0.5507        | -0.6510          | 0.5396             | 0.1003          | -1.3021        | -1.1014      | 282.3183        | 313.4974      | 1.4682   | -0.6666        | 0.3074          |
| 0.6379        | 2.9866 | 501  | 2.0035          | -0.6455        | -0.7620          | 0.6115             | 0.1164          | -1.5240        | -1.2911      | 259.2041        | 292.7468      | 1.6440   | -0.6769        | 0.3357          |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0