---
library_name: transformers
base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
tags:
- alignment-handbook
- simpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: llama-3-8b-base-simpo-8xh200
  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-base-simpo-8xh200

This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0269
- Rewards/chosen: -2.9880
- Rewards/rejected: -4.0573
- Rewards/accuracies: 0.7379
- Rewards/margins: 1.0692
- Logps/rejected: -2.0286
- Logps/chosen: -1.4940
- Logits/rejected: -0.7413
- Logits/chosen: -0.7546

## 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: 6e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 2.1958        | 0.4188 | 200  | 1.0818          | -2.4141        | -3.2133          | 0.6935             | 0.7991          | -1.6066        | -1.2071      | -0.6654         | -0.6648       |
| 2.1186        | 0.8377 | 400  | 1.0269          | -2.9880        | -4.0573          | 0.7379             | 1.0692          | -2.0286        | -1.4940      | -0.7413         | -0.7546       |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4