DCAgent / g1_subagent_e1_gpt_long_tacc

huggingface.co
Total runs: 16
24-hour runs: 2
7-day runs: 3
30-day runs: 9
Model's Last Updated: April 16 2026
text-generation

Introduction of g1_subagent_e1_gpt_long_tacc

Model Details of g1_subagent_e1_gpt_long_tacc

sft__g1_subagent_e1_gpt_long_d1_original_40k_glm47_traces__Qwen3-8B

This model is a fine-tuned version of Qwen/Qwen3-8B on the DCAgent/g1_subagent_e1_gpt_long_d1_original_40k_glm47_traces 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
  • total_train_batch_size: 16
  • total_eval_batch_size: 128
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 7.0
Training results
Framework versions
  • Transformers 4.57.3
  • Pytorch 2.9.0+cu128
  • Datasets 4.4.1
  • Tokenizers 0.22.1

Runs of DCAgent g1_subagent_e1_gpt_long_tacc on huggingface.co

16
Total runs
2
24-hour runs
1
3-day runs
3
7-day runs
9
30-day runs

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g1_subagent_e1_gpt_long_tacc install

g1_subagent_e1_gpt_long_tacc is an open source model from GitHub that offers a free installation service, and any user can find g1_subagent_e1_gpt_long_tacc on GitHub to install. At the same time, huggingface.co provides the effect of g1_subagent_e1_gpt_long_tacc install, users can directly use g1_subagent_e1_gpt_long_tacc installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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