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

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co./google/gemma-7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5398
- Rewards/chosen: -0.0540
- Rewards/rejected: -0.0625
- Rewards/accuracies: 0.5396
- Rewards/margins: 0.0085
- Logps/rejected: -1.2503
- Logps/chosen: -1.0803
- Logits/rejected: 271.8756
- Logits/chosen: 300.6891
- Nll Loss: 1.4724
- Log Odds Ratio: -0.6945
- Log Odds Chosen: 0.2937

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.441         | 0.9955 | 167  | 1.4762          | -0.0510        | -0.0574          | 0.5324             | 0.0064          | -1.1485        | -1.0204      | 290.1581        | 318.9965      | 1.4310   | -0.6990        | 0.1934          |
| 1.0908        | 1.9970 | 335  | 1.4250          | -0.0497        | -0.0576          | 0.5324             | 0.0079          | -1.1528        | -0.9950      | 285.8206        | 314.6779      | 1.3697   | -0.6970        | 0.2360          |
| 0.5724        | 2.9866 | 501  | 1.5398          | -0.0540        | -0.0625          | 0.5396             | 0.0085          | -1.2503        | -1.0803      | 271.8756        | 300.6891      | 1.4724   | -0.6945        | 0.2937          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1