cuong1692001/Terminal-complete-8k
The cuong1692001/Terminal_complete_8k is an 8 billion parameter language model fine-tuned from Qwen/Qwen3-8B. This model is optimized for specific tasks based on the 'qwen_data_complete' dataset, offering specialized performance for its intended applications. With a context length of 32768 tokens, it is designed for scenarios requiring extensive contextual understanding.
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Model Overview
The cuong1692001/Terminal_complete_8k is an 8 billion parameter language model, fine-tuned from the robust Qwen/Qwen3-8B architecture. This model has undergone specialized training on the qwen_data_complete dataset, indicating an optimization for particular use cases and data patterns.
Key Characteristics
- Base Model: Fine-tuned from Qwen/Qwen3-8B.
- Parameter Count: 8 billion parameters.
- Context Length: Supports a substantial context window of 32768 tokens, enabling processing of longer inputs and maintaining conversational coherence over extended interactions.
- Training Data: Specialized training on the
qwen_data_completedataset, suggesting tailored performance for tasks aligned with this data.
Training Details
The model was trained using the following hyperparameters:
- Learning Rate: 1e-05
- Optimizer: AdamW with betas=(0.9, 0.999) and epsilon=1e-08.
- Scheduler: Cosine learning rate scheduler.
- Epochs: 2.0 epochs.
- Batch Size: A total training batch size of 4 across 4 GPUs.
Intended Use Cases
While specific intended uses are not detailed, the fine-tuning on a dedicated dataset implies suitability for tasks where the qwen_data_complete dataset is relevant. Its large context window makes it potentially useful for applications requiring deep contextual understanding or processing of lengthy documents.