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full_sft_qwen2-5_7b_openr1_…/README.md
ModelHub XC fb735bc055 初始化项目,由ModelHub XC社区提供模型
Model: Pentland/full_sft_qwen2-5_7b_openr1_3k_context8k
Source: Original Platform
2026-08-14 21:54:03 +08:00

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---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-7B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: full_sft_qwen2-5_7b_openr1_3k_context8k
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. -->
# full_sft_qwen2-5_7b_openr1_3k_context8k
This model is a fine-tuned version of [/data2/cwli16/share-models/Qwen2.5-7B-Base](https://huggingface.co//data2/cwli16/share-models/Qwen2.5-7B-Base) on the openr1_math_alpaca 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- total_eval_batch_size: 48
- 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: 3.0
### Training results
### Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.22.1