KKHYA/qwen3-1.7b-fft-if
The KKHYA/qwen3-1.7b-fft-if model is a 2 billion parameter language model, fine-tuned from Qwen/Qwen3-1.7B. It was trained on a diverse set of datasets including mft_tulu3_personas_if, mft_oasst1, mft_oasst2, mft_coconot, mft_aya, and mft_daring_anteater. This model is designed for general language generation tasks, leveraging its fine-tuning on multiple instruction-following and conversational datasets.
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Model Overview
This model, KKHYA/qwen3-1.7b-fft-if, is a fine-tuned variant of the 2 billion parameter Qwen3-1.7B base model. It has been specifically adapted through further training on a combination of diverse datasets, aiming to enhance its conversational and instruction-following capabilities.
Key Training Details
The model underwent fine-tuning using a comprehensive set of datasets, including:
mft_tulu3_personas_ifmft_oasst1mft_oasst2mft_coconotmft_ayamft_daring_anteater
Training was conducted with a learning rate of 1e-05, a total batch size of 128, and utilized a cosine learning rate scheduler over 2 epochs. The optimizer used was ADAMW_TORCH_FUSED.
Potential Use Cases
Given its fine-tuning on instruction-following and conversational datasets, this model is likely suitable for:
- General-purpose text generation: Creating coherent and contextually relevant text.
- Instruction following: Responding to prompts and instructions effectively.
- Conversational AI: Engaging in dialogue and generating human-like responses.