Files
ModelHub XC 24073ff9d6 初始化项目,由ModelHub XC社区提供模型
Model: jackf857/qwen3-8b-base-simpo-ultrafeedback-4xH200-batch-128
Source: Original Platform
2026-05-16 14:41:21 +08:00

77 lines
2.6 KiB
Markdown

---
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
should probably proofread and complete it, then remove this comment. -->
# 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