---
library_name: transformers
license: other
base_model: Qwen/Qwen3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: sft__Kimi-2-5-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-32k-reward1-Kimi-2-5-r2e
  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. -->

# sft__Kimi-2-5-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-32k-reward1-Kimi-2-5-r2e

This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the /e/data1/datasets/playground/ot/hf_hub/datasets--penfever--Kimi-2.5-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-32k-reward1/snapshots/80469f6065c0a97bc567f76132a4a6b5b2b1e181_thinking_preprocessed and the /e/data1/datasets/playground/ot/hf_hub/datasets--penfever--Kimi-2.5-r2egym_sandboxes-maxeps-32k-reward1/snapshots/6eecc31462c33c0a43e5c130092daf9a8456b06f_thinking_preprocessed datasets.

## 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: 4e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 3
- total_train_batch_size: 96
- total_eval_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7.0

### Training results



### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.1+cu130
- Datasets 4.7.0
- Tokenizers 0.22.2
