Model Overview

This model, laion/r2egym-31600__Qwen3-8B, is an 8 billion parameter language model derived from the Qwen/Qwen3-8B base architecture. It has been specifically fine-tuned on the /e/data1/datasets/playground/ot/hf_hub/datasets--laion--r2egym-unified-31600 dataset.

Training Details

The fine-tuning process involved several key hyperparameters:

• Learning Rate: 4e-05
• Batch Size: A train_batch_size of 1 and eval_batch_size of 8 were used, with a total_train_batch_size of 96 across 32 devices.
• Optimizer: AdamW_Torch_Fused with betas=(0.9, 0.98) and epsilon=1e-08.
• Scheduler: A cosine learning rate scheduler with a warmup ratio of 0.1.
• Epochs: The model was trained for 7.0 epochs.

Framework Versions

The training environment utilized:

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

Potential Use Cases

Given its fine-tuning on a specific dataset, this model is likely optimized for tasks related to the content and structure of the r2egym-unified-31600 dataset. Developers should evaluate its performance on tasks that align with this dataset's characteristics.