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ModelHub XC d238cc8b5c 初始化项目,由ModelHub XC社区提供模型
Model: jackf857/llama-3-8b-base-margin-dpo-hh-4xh100
Source: Original Platform
2026-04-24 16:00:00 +08:00

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---
library_name: transformers
license: llama3
base_model: W-61/llama-3-8b-base-hh-harmless-sft-4xh100
tags:
- alignment-handbook
- margin-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: llama-3-8b-base-margin-dpo-hh-4xh100
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. -->
# llama-3-8b-base-margin-dpo-hh-4xh100
This model is a fine-tuned version of [W-61/llama-3-8b-base-hh-harmless-sft-4xh100](https://huggingface.co/W-61/llama-3-8b-base-hh-harmless-sft-4xh100) on the Anthropic/hh-rlhf dataset.
## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- 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
### Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4