This model is a fine-tuned version of Qwen/Qwen3-8B on the /leonardo_work/AIFAC_5C0_290/bfeuer00/data/hub/datasets--DCAgent--g1_selective_top8_diverse_100000_glm47_traces/snapshots/ea398c13e5f96bd45e7d2f6fd583bd1c00ef4f71_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: 4e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 32
gradient_accumulation_steps: 3
total_train_batch_size: 96
total_eval_batch_size: 256
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+cu128
Datasets 4.4.1
Tokenizers 0.22.2

laion/g1_selective_top8_diverse_100000_glm47_traces

sft__g1_selective_top8_diverse_100000_glm47_traces__40-0__Qwen3-8B

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

laion/
g1_selective_top8_diverse_100000_glm47_traces

sft__g1_selective_top8_diverse_100000_glm47_traces40-0Qwen3-8B