---
library_name: transformers
base_model: jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128
tags:
- alignment-handbook
- simpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: qwen3-8b-base-simpo-ultrafeedback-4xh200-batch-128
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# qwen3-8b-base-simpo-ultrafeedback-4xh200-batch-128

This model is a fine-tuned version of [jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128](https://huggingface.co/jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0770
- Rewards/chosen: -2.1095
- Rewards/rejected: -2.9493
- Rewards/accuracies: 0.6660
- Rewards/margins: 0.8398
- Logps/rejected: -1.4746
- Logps/chosen: -1.0548
- Logits/rejected: 2.1566
- Logits/chosen: 2.1386

## 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: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 9.1298        | 0.4188 | 200  | 1.1165          | -2.0802        | -2.7440          | 0.6360             | 0.6638          | -1.3720        | -1.0401      | 2.1249          | 2.1120        |
| 8.8992        | 0.8377 | 400  | 1.0770          | -2.1095        | -2.9493          | 0.6660             | 0.8398          | -1.4746        | -1.0548      | 2.1566          | 2.1386        |


### Framework versions

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