README.md

---
library_name: transformers
base_model: Jennny/llama3_8b_sft_ultrafb
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_8b_helpful_rm_full
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama3_8b_helpful_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: 0.1930
- Accuracy: 0.926

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.2039        | 0.4320 | 50   | 0.2106          | 0.912    |
| 0.2018        | 0.8639 | 100  | 0.1930          | 0.926    |


### Framework versions

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