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---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-Math-7B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: prm_qwen25_math_version3_subsample_hf
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. -->
# prm_qwen25_math_version3_subsample_hf
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-7B-Instruct) on the prm_conversations_prm_version3_math+webinstructsub-mcq+webinstructsub-oe+apps+gsm_mix_ref_subsample_hf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1639
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- 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: 0.05
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.2317 | 0.1127 | 500 | 0.2231 |
| 0.2003 | 0.2253 | 1000 | 0.2006 |
| 0.166 | 0.3380 | 1500 | 0.1876 |
| 0.1755 | 0.4506 | 2000 | 0.1788 |
| 0.1612 | 0.5633 | 2500 | 0.1725 |
| 0.1607 | 0.6759 | 3000 | 0.1680 |
| 0.1655 | 0.7886 | 3500 | 0.1653 |
| 0.1486 | 0.9012 | 4000 | 0.1641 |
### Framework versions
- Transformers 4.45.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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