---
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: llama3_rm
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama3_rm

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3581
- Accuracy: 0.8443

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8063        | 0.0705 | 10   | 0.6141          | 0.7339   |
| 0.5355        | 0.1410 | 20   | 0.5117          | 0.7604   |
| 0.4811        | 0.2115 | 30   | 0.4766          | 0.7719   |
| 0.4922        | 0.2819 | 40   | 0.4512          | 0.7792   |
| 0.4919        | 0.3524 | 50   | 0.4428          | 0.8      |
| 0.476         | 0.4229 | 60   | 0.4174          | 0.8083   |
| 0.3965        | 0.4934 | 70   | 0.4047          | 0.8161   |
| 0.3523        | 0.5639 | 80   | 0.3918          | 0.8224   |
| 0.455         | 0.6344 | 90   | 0.3794          | 0.8344   |
| 0.4096        | 0.7048 | 100  | 0.3682          | 0.8396   |
| 0.3726        | 0.7753 | 110  | 0.3636          | 0.8417   |
| 0.3802        | 0.8458 | 120  | 0.3600          | 0.8448   |
| 0.3908        | 0.9163 | 130  | 0.3585          | 0.8427   |
| 0.4002        | 0.9868 | 140  | 0.3581          | 0.8443   |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.1.2+cu121
- Datasets 4.4.1
- Tokenizers 0.19.1