---
license: other
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
base_model: google/gemma-2b
metrics:
- accuracy
model-index:
- name: gemma_2b_oasst1_reward_model
  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_2b_oasst1_reward_model

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: 0.4481
- Accuracy: 0.8036

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4696        | 0.38  | 100  | 0.5181          | 0.7542   |
| 0.4327        | 0.76  | 200  | 0.4738          | 0.8025   |
| 0.3946        | 1.15  | 300  | 0.5145          | 0.7924   |
| 0.3372        | 1.53  | 400  | 0.5370          | 0.7890   |
| 0.3618        | 1.91  | 500  | 0.4481          | 0.8036   |
| 0.3292        | 2.29  | 600  | 0.4799          | 0.7991   |
| 0.4514        | 2.68  | 700  | 0.4763          | 0.8013   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2