laion/Kimi-K2T-neulab-agenttuning-mind2web-sandboxes-maxeps-32k

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Kimi-K2T-neulab-agenttuning-mind2web-sandboxes-maxeps-32k

This model is a fine-tuned version of Qwen/Qwen3-8B on the open-athena/Kimi-K2T-neulab-agenttuning-mind2web-sandboxes-maxeps-32k_neulab-agenttuning-db-sandboxes 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: 8
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 64
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 0.22.2