---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: rm_llama3_8B_helpsteer2
  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. -->

# rm_llama3_8B_helpsteer2

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1203
- Accuracy: 0.6339

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8471        | 0.1572 | 50   | 0.7326          | 0.5819   |
| 0.7455        | 0.3145 | 100  | 0.6821          | 0.5549   |
| 0.7059        | 0.4717 | 150  | 0.6642          | 0.6050   |
| 0.6926        | 0.6289 | 200  | 0.6707          | 0.5915   |
| 0.6683        | 0.7862 | 250  | 0.6506          | 0.6320   |
| 0.6727        | 0.9434 | 300  | 0.6456          | 0.6224   |
| 0.629         | 1.1006 | 350  | 0.6218          | 0.6551   |
| 0.5446        | 1.2579 | 400  | 0.6604          | 0.6281   |
| 0.5377        | 1.4151 | 450  | 0.6345          | 0.6455   |
| 0.5555        | 1.5723 | 500  | 0.6145          | 0.6320   |
| 0.5645        | 1.7296 | 550  | 0.6178          | 0.6474   |
| 0.5392        | 1.8868 | 600  | 0.6323          | 0.6532   |
| 0.4505        | 2.0440 | 650  | 0.7539          | 0.6455   |
| 0.1406        | 2.2013 | 700  | 1.0884          | 0.6339   |
| 0.1487        | 2.3585 | 750  | 1.1136          | 0.6339   |
| 0.1493        | 2.5157 | 800  | 1.1202          | 0.6358   |
| 0.1259        | 2.6730 | 850  | 1.1253          | 0.6320   |
| 0.1382        | 2.8302 | 900  | 1.1189          | 0.6320   |
| 0.1448        | 2.9874 | 950  | 1.1203          | 0.6339   |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.2.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1