cuong1692001/Terminal-complete-4k
Terminal_complete_4k is an 8 billion parameter language model fine-tuned from Qwen/Qwen3-8B by cuong1692001. This model is trained on the qwen_data_complete dataset, suggesting a focus on comprehensive language understanding and generation. It is designed for general language tasks, leveraging the robust architecture of the Qwen3 series.
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Model Overview
Terminal_complete_4k is an 8 billion parameter language model developed by cuong1692001. It is a fine-tuned variant of the robust Qwen/Qwen3-8B architecture, indicating a strong foundation in general-purpose language understanding and generation. The model was trained using the qwen_data_complete dataset, which suggests an emphasis on comprehensive data for enhanced performance across various linguistic tasks.
Training Details
The model underwent fine-tuning with specific hyperparameters to optimize its performance. Key training parameters included a learning rate of 1e-05, a train_batch_size of 1, and an eval_batch_size of 8. Training was conducted for 2.0 epochs using a multi-GPU setup with 4 devices, employing the AdamW optimizer and a cosine learning rate scheduler. The training environment utilized Transformers 5.6.0, Pytorch 2.11.0+cu130, Datasets 4.0.0, and Tokenizers 0.22.2.
Intended Use Cases
While specific intended uses and limitations are not detailed in the provided information, as a fine-tuned version of Qwen3-8B, Terminal_complete_4k is generally suitable for a wide range of natural language processing applications. Its foundation suggests capabilities in areas such as text generation, summarization, question answering, and conversational AI, particularly where comprehensive language understanding is beneficial.