---
library_name: transformers
license: other
base_model: deepseek-ai/DeepSeek-Prover-V2-7B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: deepseek-prover-v2-7b-lean-cpt-sft-feedback-32k
  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. -->

# deepseek-prover-v2-7b-lean-cpt-sft-feedback-32k

This model is a fine-tuned version of [deepseek-ai/DeepSeek-Prover-V2-7B](https://huggingface.co/deepseek-ai/DeepSeek-Prover-V2-7B) on the lean_sft_feedback dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0217

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- 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: 0.05
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.0399        | 0.0827 | 1000  | 0.0343          |
| 0.0261        | 0.1654 | 2000  | 0.0284          |
| 0.0283        | 0.2481 | 3000  | 0.0264          |
| 0.0228        | 0.3308 | 4000  | 0.0250          |
| 0.0215        | 0.4135 | 5000  | 0.0242          |
| 0.0216        | 0.4962 | 6000  | 0.0235          |
| 0.0228        | 0.5789 | 7000  | 0.0229          |
| 0.0214        | 0.6616 | 8000  | 0.0225          |
| 0.0232        | 0.7444 | 9000  | 0.0221          |
| 0.0205        | 0.8271 | 10000 | 0.0219          |
| 0.0214        | 0.9098 | 11000 | 0.0218          |
| 0.0241        | 0.9925 | 12000 | 0.0217          |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu129
- Datasets 3.6.0
- Tokenizers 0.22.1
