---
library_name: transformers
base_model: Jennny/llama3_8b_sft_ultrafb
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_8b_general_rm_full
  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_general_rm_full

This model is a fine-tuned version of [Jennny/llama3_8b_sft_ultrafb](https://huggingface.co/Jennny/llama3_8b_sft_ultrafb) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2676
- Accuracy: 0.8858

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 512
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3173        | 0.1549 | 50   | 0.3212          | 0.8622   |
| 0.3037        | 0.3098 | 100  | 0.2959          | 0.8742   |
| 0.2982        | 0.4647 | 150  | 0.3012          | 0.8735   |
| 0.2857        | 0.6196 | 200  | 0.2818          | 0.8823   |
| 0.2773        | 0.7744 | 250  | 0.2716          | 0.8853   |
| 0.2691        | 0.9293 | 300  | 0.2676          | 0.8858   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3