---
library_name: transformers
base_model: Jennny/llama3_8b_sft_helpsteer
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_8b_helpsteer_correct_rm
  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. -->

# llama3_8b_helpsteer_correct_rm

This model is a fine-tuned version of [Jennny/llama3_8b_sft_helpsteer](https://huggingface.co/Jennny/llama3_8b_sft_helpsteer) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5813
- Accuracy: 0.5847

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1608        | 0.1882 | 10   | 1.1481          | 0.5847   |
| 0.128         | 0.3765 | 20   | 0.8165          | 0.6045   |
| 0.1509        | 0.5647 | 30   | 0.7681          | 0.6271   |
| 0.1323        | 0.7529 | 40   | 0.8492          | 0.5650   |
| 0.0856        | 0.9412 | 50   | 0.9250          | 0.6073   |
| 0.0013        | 1.1129 | 60   | 1.2136          | 0.6073   |
| 0.0088        | 1.3012 | 70   | 1.7243          | 0.5593   |
| 0.034         | 1.4894 | 80   | 1.7962          | 0.5650   |
| 0.0083        | 1.6776 | 90   | 1.6045          | 0.5763   |
| 0.0001        | 1.8659 | 100  | 1.5813          | 0.5847   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1