peft safetensors trl reward-trainer generated_from_trainer base_model:google/gemma-2b license:other region:us
---
license: other
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
base_model: google/gemma-2b
metrics:
- accuracy
model-index:
- name: gemma_2b_social_reasoning_reward_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gemma_2b_social_reasoning_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: 0.6131
- Accuracy: 0.6713

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7962        | 0.24  | 10   | 0.6976          | 0.6077   |
| 0.6657        | 0.48  | 20   | 0.6464          | 0.6217   |
| 0.6334        | 0.72  | 30   | 0.6330          | 0.6392   |
| 0.6434        | 0.96  | 40   | 0.6218          | 0.6427   |
| 0.5745        | 1.2   | 50   | 0.6119          | 0.6567   |
| 0.5813        | 1.44  | 60   | 0.6282          | 0.6445   |
| 0.5822        | 1.68  | 70   | 0.6350          | 0.6585   |
| 0.5914        | 1.92  | 80   | 0.6294          | 0.6550   |
| 0.5386        | 2.16  | 90   | 0.6341          | 0.6550   |
| 0.5142        | 2.4   | 100  | 0.6330          | 0.6567   |
| 0.4906        | 2.63  | 110  | 0.6313          | 0.6620   |
| 0.5079        | 2.87  | 120  | 0.6309          | 0.6637   |


### Framework versions

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