---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- simonycl/Meta-Llama-3-8B-Instruct_ultrafeedback-Meta-Llama-3-8B-Instruct-annotate-start-0-end-1.0-judge-5
model-index:
- name: llama-3-8b-instruct-agg-judge
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama-3-8b-instruct-agg-judge

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 simonycl/Meta-Llama-3-8B-Instruct_ultrafeedback-Meta-Llama-3-8B-Instruct-annotate-start-0-end-1.0-judge-5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6390
- Rewards/chosen: -1.0532
- Rewards/rejected: -1.3037
- Rewards/accuracies: 0.6057
- Rewards/margins: 0.2506
- Logps/rejected: -280.7787
- Logps/chosen: -256.8969
- Logits/rejected: -1.4905
- Logits/chosen: -1.5260

## 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: 5e-07
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6265        | 0.4264 | 400  | 0.6455          | -0.7831        | -0.9487          | 0.6504             | 0.1655          | -245.2767      | -229.8961    | -1.3679         | -1.4091       |
| 0.6053        | 0.8529 | 800  | 0.6390          | -1.0532        | -1.3037          | 0.6057             | 0.2506          | -280.7787      | -256.8969    | -1.4905         | -1.5260       |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.0