This model is a fine-tuned version of Qwen/Qwen3-8B on the /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--neulab-code-feedback-sandboxes_glm_4.7_traces_jupiter/snapshots/e815aba2c9ff5d91161edf385c1deba77cd72e9e_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: 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 4.57.6
Pytorch 2.9.1+cu130
Datasets 4.7.0
Tokenizers 0.22.2

DCAgent/a1-code_feedback

sft_a1_code_feedback__Qwen3-8B

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

DCAgent/
a1-code_feedback