a1-orca_agentinstruct

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sft_a1_orca_agentinstruct__Qwen3-8B

This model is a fine-tuned version of Qwen/Qwen3-8B on the /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--neulab-orca-agentinstruct-sandboxes_glm_4.7_traces_jupiter/snapshots/4f903c7c272d85ea054d297e95b2bad92a00eea2_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