---
library_name: transformers
license: gemma
base_model: google/gemma-7b
tags:
- trl
- orpo
- generated_from_trainer
model-index:
- name: gemma-7b-borpo-low-quality-v4
  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-v4

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9080
- Rewards/chosen: -0.6019
- Rewards/rejected: -0.7507
- Rewards/accuracies: 0.6259
- Rewards/margins: 0.1488
- Logps/rejected: -1.5015
- Logps/chosen: -1.2038
- Logits/rejected: 247.6263
- Logits/chosen: 282.0085
- Nll Loss: 1.5545
- Log Odds Ratio: -0.6477
- Log Odds Chosen: 0.4230

## 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-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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.8238        | 0.9955 | 167  | 1.8176          | -0.5378        | -0.6319          | 0.5468             | 0.0941          | -1.2637        | -1.0755      | 293.2744        | 322.6454      | 1.4783   | -0.6631        | 0.2616          |
| 1.3092        | 1.9970 | 335  | 1.7560          | -0.5202        | -0.6309          | 0.5324             | 0.1106          | -1.2617        | -1.0405      | 279.0659        | 309.3900      | 1.4054   | -0.6637        | 0.3224          |
| 0.6827        | 2.9866 | 501  | 1.9080          | -0.6019        | -0.7507          | 0.6259             | 0.1488          | -1.5015        | -1.2038      | 247.6263        | 282.0085      | 1.5545   | -0.6477        | 0.4230          |


### Framework versions

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