laion/exp-psu-swesmith-1K_glm_4-7_traces_jupiter__0-98__Qwen3-8B
The laion/exp-psu-swesmith-1K_glm_4-7_traces_jupiter__0-98__Qwen3-8B is an 8 billion parameter language model, fine-tuned from the Qwen3-8B architecture. This model was specifically trained on the /e/data1/datasets/playground/ot/hf_hub/datasets--DCAgent--exp-psu-swesmith-1K_glm_4.7_traces_jupiter/snapshots/24c8342833108c3a15a23b64f37b83ff7e65efa4_thinking_preprocessed dataset. It is designed for tasks related to its specific fine-tuning data, offering specialized performance within that domain.
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Model Overview
This model, laion/exp-psu-swesmith-1K_glm_4-7_traces_jupiter__0-98__Qwen3-8B, is an 8 billion parameter language model derived from the Qwen3-8B architecture. It has undergone a specific fine-tuning process to adapt its capabilities to a particular dataset.
Key Characteristics
- Base Model: Fine-tuned from Qwen/Qwen3-8B.
- Fine-tuning Dataset: Trained on the
/e/data1/datasets/playground/ot/hf_hub/datasets--DCAgent--exp-psu-swesmith-1K_glm_4.7_traces_jupiter/snapshots/24c8342833108c3a15a23b64f37b83ff7e65efa4_thinking_preprocesseddataset. - Training Hyperparameters: Utilized a learning rate of 4e-05, a total batch size of 96 (with gradient accumulation), and trained for 7 epochs using the AdamW optimizer with a cosine learning rate scheduler.
Intended Use Cases
Given its fine-tuning on a specific dataset, this model is best suited for applications and research that align with the characteristics and domain of the exp-psu-swesmith-1K_glm_4.7_traces_jupiter dataset. Developers should consider its specialized training for tasks requiring nuanced understanding or generation within that particular data distribution.