---
license: apache-2.0
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
base_model: AI-Sweden-Models/gpt-sw3-1.3b
model-index:
- name: gpt1B_reward_test
  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. -->

# gpt1B_reward_test

This model is a fine-tuned version of [AI-Sweden-Models/gpt-sw3-1.3b](https://huggingface.co/AI-Sweden-Models/gpt-sw3-1.3b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6367
- Accuracy: 0.6504

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6878        | 0.04  | 200  | 0.6850          | 0.5791   |
| 0.6724        | 0.08  | 400  | 0.6740          | 0.6024   |
| 0.6611        | 0.13  | 600  | 0.6703          | 0.6081   |
| 0.6435        | 0.17  | 800  | 0.6773          | 0.6036   |
| 0.6787        | 0.21  | 1000 | 0.6544          | 0.6189   |
| 0.7166        | 0.25  | 1200 | 0.6697          | 0.6223   |
| 0.614         | 0.3   | 1400 | 0.6590          | 0.6250   |
| 0.6279        | 0.34  | 1600 | 0.6422          | 0.6343   |
| 0.6185        | 0.38  | 1800 | 0.6427          | 0.6389   |
| 0.5539        | 0.42  | 2000 | 0.6459          | 0.6390   |
| 0.5988        | 0.47  | 2200 | 0.6485          | 0.6379   |
| 0.6096        | 0.51  | 2400 | 0.6570          | 0.6439   |
| 0.5898        | 0.55  | 2600 | 0.6381          | 0.6441   |
| 0.6366        | 0.59  | 2800 | 0.6479          | 0.6389   |
| 0.6457        | 0.64  | 3000 | 0.6397          | 0.6490   |
| 0.6171        | 0.68  | 3200 | 0.6476          | 0.6467   |
| 0.5262        | 0.72  | 3400 | 0.6506          | 0.6458   |
| 0.5723        | 0.76  | 3600 | 0.6467          | 0.6471   |
| 0.6194        | 0.81  | 3800 | 0.6393          | 0.6480   |
| 0.5946        | 0.85  | 4000 | 0.6375          | 0.6490   |
| 0.5868        | 0.89  | 4200 | 0.6366          | 0.6503   |
| 0.5905        | 0.93  | 4400 | 0.6367          | 0.6505   |
| 0.5651        | 0.97  | 4600 | 0.6367          | 0.6504   |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.1
- Pytorch 2.2.0+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2