| | --- |
| | library_name: transformers |
| | license: other |
| | base_model: Qwen/Qwen2.5-Math-7B-Instruct |
| | tags: |
| | - llama-factory |
| | - full |
| | - generated_from_trainer |
| | model-index: |
| | - name: GenPRM-78k-train-5:5-decontamination |
| | 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. --> |
| |
|
| | # GenPRM-78k-train-5:5-decontamination |
| |
|
| | This model is a fine-tuned version of [/data1/model/Qwen2.5-Math-7B-Instruct](https://huggingface.co//data1/model/Qwen2.5-Math-7B-Instruct) on the GenPRM-78k-train-5:5-decontamination dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2910 |
| |
|
| | ## 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-06 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 8 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 64 |
| | - total_eval_batch_size: 8 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.03 |
| | - num_epochs: 1 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 0.3951 | 0.0823 | 100 | 0.3771 | |
| | | 0.3471 | 0.1647 | 200 | 0.3431 | |
| | | 0.3295 | 0.2470 | 300 | 0.3266 | |
| | | 0.3162 | 0.3294 | 400 | 0.3161 | |
| | | 0.3143 | 0.4117 | 500 | 0.3084 | |
| | | 0.3054 | 0.4940 | 600 | 0.3029 | |
| | | 0.3031 | 0.5764 | 700 | 0.2985 | |
| | | 0.2988 | 0.6587 | 800 | 0.2953 | |
| | | 0.2965 | 0.7410 | 900 | 0.2932 | |
| | | 0.2935 | 0.8234 | 1000 | 0.2918 | |
| | | 0.2975 | 0.9057 | 1100 | 0.2911 | |
| | | 0.304 | 0.9881 | 1200 | 0.2910 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.45.2 |
| | - Pytorch 2.4.0+cu121 |
| | - Datasets 2.21.0 |
| | - Tokenizers 0.20.1 |
| | |
