---
license: mit
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: google/gemma-2b
model-index:
- name: gemma-7b-lora-distilabel-intel-orca-dpo-pairs
  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-lora-distilabel-intel-orca-dpo-pairs

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4641
- Rewards/chosen: -0.2842
- Rewards/rejected: -2.0677
- Rewards/accuracies: 0.8414
- Rewards/margins: 1.7835
- Logps/rejected: -294.6812
- Logps/chosen: -246.1420
- Logits/rejected: -29.7875
- Logits/chosen: -27.6122

## 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: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6333        | 0.19  | 250  | 0.5221          | -0.4649        | -1.1235          | 0.8196             | 0.6586          | -285.2397      | -247.9492    | -29.5102        | -27.3832      |
| 0.4697        | 0.39  | 500  | 0.4819          | -0.5572        | -2.0261          | 0.8394             | 1.4689          | -294.2652      | -248.8721    | -29.5979        | -27.4182      |
| 0.4471        | 0.58  | 750  | 0.4814          | -0.5104        | -2.3183          | 0.8418             | 1.8079          | -297.1878      | -248.4040    | -29.6888        | -27.5182      |
| 0.4477        | 0.78  | 1000 | 0.4744          | -0.3874        | -2.2429          | 0.8418             | 1.8555          | -296.4334      | -247.1736    | -29.7387        | -27.5680      |
| 0.458         | 0.97  | 1250 | 0.4641          | -0.2842        | -2.0677          | 0.8414             | 1.7835          | -294.6812      | -246.1420    | -29.7875        | -27.6122      |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.0
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2