---
license: gemma
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
base_model: google/gemma-2b
model-index:
- name: RM-HH-Mix_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# RM-HH-Mix_harmless_gpt3_20000_gemma2b_shuffleFalse_extractchosenFalse

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: 0.0445
- Accuracy: 0.9815

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8191        | 0.06  | 250  | 0.5824          | 0.695    |
| 0.6294        | 0.11  | 500  | 0.1346          | 0.953    |
| 0.5811        | 0.17  | 750  | 0.0888          | 0.9705   |
| 0.5753        | 0.22  | 1000 | 0.0684          | 0.975    |
| 0.5539        | 0.28  | 1250 | 0.0588          | 0.979    |
| 0.5764        | 0.33  | 1500 | 0.0595          | 0.9785   |
| 0.5261        | 0.39  | 1750 | 0.0558          | 0.979    |
| 0.5423        | 0.44  | 2000 | 0.0533          | 0.9795   |
| 0.5261        | 0.5   | 2250 | 0.0501          | 0.98     |
| 0.5363        | 0.56  | 2500 | 0.0485          | 0.98     |
| 0.5051        | 0.61  | 2750 | 0.0472          | 0.981    |
| 0.5157        | 0.67  | 3000 | 0.0509          | 0.9795   |
| 0.5368        | 0.72  | 3250 | 0.0507          | 0.9785   |
| 0.5281        | 0.78  | 3500 | 0.0467          | 0.981    |
| 0.5005        | 0.83  | 3750 | 0.0450          | 0.9815   |
| 0.5239        | 0.89  | 4000 | 0.0445          | 0.9815   |
| 0.5111        | 0.94  | 4250 | 0.0445          | 0.9815   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2