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taskmaster2-gpt5mini – Dataset by DCAgent | AlphaNeural AI

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DCAgent/
taskmaster2-gpt5mini

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taskmaster2-gpt5mini

This model is a fine-tuned version of Qwen/Qwen3-8B on the DCAgent/taskmaster2-gpt5mini dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 4e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 16
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 128
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5.0

Training results

Framework versions

Transformers 4.55.0
Pytorch 2.7.0+cu128
Datasets 3.6.0
Tokenizers 0.21.1