viamr-project/qwen3-1.7b-amr-20260705-0434
The viamr-project/qwen3-1.7b-amr-20260705-0434 is a 2 billion parameter model with a 32768 token context length, developed by viamr-project. This model is specifically evaluated for its performance on 1898 samples, achieving an average F1 score of 76.93, an average precision of 76.71, and an average recall of 77.79. It is designed for tasks requiring robust evaluation metrics, indicating its suitability for applications where precise performance measurement is critical.
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Model Overview
The viamr-project/qwen3-1.7b-amr-20260705-0434 is a 2 billion parameter language model developed by viamr-project, featuring an extensive context length of 32768 tokens. This model has undergone specific evaluation against 1898 samples, demonstrating a balanced performance across key metrics.
Key Capabilities
- Performance Metrics: Achieves an average F1 score of 76.93, an average precision of 76.71, and an average recall of 77.79.
- Context Handling: Supports a large context window of 32768 tokens, enabling processing of longer inputs and maintaining coherence over extended interactions.
Good For
- Evaluated Tasks: Suitable for applications where performance has been rigorously measured and specific F1, precision, and recall scores are relevant.
- Long-Context Applications: Ideal for use cases requiring the model to understand and generate content based on extensive input, thanks to its large context window.