---
license: gemma
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
base_model: google/gemma-2b
metrics:
- accuracy
model-index:
- name: RM-HH-AllMix_harmless_gpt3_20000_gemma2b_shuffleTrue_extractchosenTrue
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# RM-HH-AllMix_harmless_gpt3_20000_gemma2b_shuffleTrue_extractchosenTrue

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5277
- Accuracy: 0.7168

## 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: 1.41e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8315        | 0.04  | 250  | 0.7587          | 0.5337   |
| 0.7136        | 0.08  | 500  | 0.6394          | 0.6303   |
| 0.6091        | 0.13  | 750  | 0.6058          | 0.6544   |
| 0.6005        | 0.17  | 1000 | 0.5916          | 0.6634   |
| 0.5844        | 0.21  | 1250 | 0.5839          | 0.6743   |
| 0.5823        | 0.25  | 1500 | 0.5729          | 0.6796   |
| 0.5845        | 0.29  | 1750 | 0.5629          | 0.6815   |
| 0.5726        | 0.33  | 2000 | 0.5599          | 0.6833   |
| 0.5564        | 0.38  | 2250 | 0.5675          | 0.6886   |
| 0.5681        | 0.42  | 2500 | 0.5550          | 0.6912   |
| 0.5713        | 0.46  | 2750 | 0.5367          | 0.6897   |
| 0.5403        | 0.5   | 3000 | 0.5392          | 0.6980   |
| 0.5299        | 0.54  | 3250 | 0.5502          | 0.7029   |
| 0.5397        | 0.59  | 3500 | 0.5411          | 0.7025   |
| 0.5629        | 0.63  | 3750 | 0.5377          | 0.7048   |
| 0.5307        | 0.67  | 4000 | 0.5290          | 0.7119   |
| 0.5154        | 0.71  | 4250 | 0.5322          | 0.7104   |
| 0.5307        | 0.75  | 4500 | 0.5363          | 0.7123   |
| 0.5414        | 0.79  | 4750 | 0.5320          | 0.7161   |
| 0.5444        | 0.84  | 5000 | 0.5269          | 0.7194   |
| 0.4831        | 0.88  | 5250 | 0.5325          | 0.7183   |
| 0.528         | 0.92  | 5500 | 0.5281          | 0.7187   |
| 0.527         | 0.96  | 5750 | 0.5277          | 0.7168   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2