---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- alignment-handbook
- trl
- simpo
- generated_from_trainer
- trl
- simpo
- generated_from_trainer
datasets:
- yakazimir/llama3-ultrafeedback-armorm
model-index:
- name: llama3_l5_best_entropy
  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_l5_best_entropy

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the yakazimir/llama3-ultrafeedback-armorm dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4398
- Rewards/chosen: -8.4238
- Rewards/rejected: -21.7089
- Rewards/accuracies: 0.8795
- Rewards/margins: 13.2850
- Logps/rejected: -2.1709
- Logps/chosen: -0.8424
- Logits/rejected: -1.4192
- Logits/chosen: -1.5108
- Semantic Entropy: 0.8327

## 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-06
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Semantic Entropy |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:----------------:|
| 1.5778        | 0.8743 | 400  | 1.6373          | -8.6865        | -18.8603         | 0.8735             | 10.1738         | -1.8860        | -0.8687      | -1.4323         | -1.5078       | 0.8519           |
| 0.9552        | 1.7486 | 800  | 1.4402          | -8.2804        | -21.2503         | 0.8795             | 12.9699         | -2.1250        | -0.8280      | -1.4434         | -1.5360       | 0.8377           |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1