---
license: cc-by-nc-4.0
base_model: sfairXC/FsfairX-LLaMA3-RM-v0.1
tags:
- easylm
- alignment-handbook
- trl
- reward-trainer
- generated_from_trainer
datasets:
- helpsteer-rm
metrics:
- accuracy
model-index:
- name: easylm-helpsteer-rm-FsfairX-LLaMA3-RM-v0.1
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: helpsteer-rm
      type: helpsteer-rm
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.664756446991404
---

<!-- 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. -->

# easylm-helpsteer-rm-FsfairX-LLaMA3-RM-v0.1

This model is a fine-tuned version of [sfairXC/FsfairX-LLaMA3-RM-v0.1](https://huggingface.co/sfairXC/FsfairX-LLaMA3-RM-v0.1) on the helpsteer-rm dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6508
- Accuracy: 0.6648

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1