This model is a fine-tuned version of Qwen/Qwen3-8B on the /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--g1_min_episodes_e1_weighted_top4_31600_glm47_traces/snapshots/a4717e999b7f8e9ad717b435f2d4a5cc75535932_thinking_preprocessed 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: 2e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 48
gradient_accumulation_steps: 2
total_train_batch_size: 96
total_eval_batch_size: 384
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: 5.0

Training results

Framework versions

Transformers 4.57.6
Pytorch 2.9.1+cu130
Datasets 4.7.0
Tokenizers 0.22.2

DCAgent/g1_weighted_31600_8b_v2

sft_g1_weighted_31600_8b_v2__Qwen3-8B

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DCAgent/
g1_weighted_31600_8b_v2