laion/exp_tas_timeout_multiplier_1_0_traces
The laion/exp_tas_timeout_multiplier_1_0_traces model is an 8 billion parameter language model fine-tuned from Qwen/Qwen3-8B. It was trained on the DCAgent/exp_tas_timeout_multiplier_1.0_traces dataset. This model is specifically adapted for tasks related to the dataset it was fine-tuned on, suggesting specialized performance in areas like trace analysis or timeout multiplier experimentation.
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Model Overview
This model, exp_tas_timeout_multiplier_1_0_traces, is an 8 billion parameter language model derived from the Qwen/Qwen3-8B architecture. It has undergone fine-tuning on the specific DCAgent/exp_tas_timeout_multiplier_1.0_traces dataset.
Training Details
The fine-tuning process utilized the following key hyperparameters:
- Learning Rate: 4e-05
- Batch Size: 1 (train), 8 (eval)
- Gradient Accumulation: 2 steps, leading to a total effective training batch size of 16
- Optimizer: AdamW_Torch_Fused with betas=(0.9, 0.98) and epsilon=1e-08
- LR Scheduler: Cosine type with a warmup ratio of 0.1
- Epochs: 7.0
Potential Use Cases
Given its fine-tuning on the DCAgent/exp_tas_timeout_multiplier_1.0_traces dataset, this model is likely best suited for applications that involve:
- Analyzing or generating content related to trace data.
- Tasks involving timeout multiplier configurations or similar experimental parameters.
Further details on specific intended uses and limitations would require more information about the DCAgent/exp_tas_timeout_multiplier_1.0_traces dataset itself.