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airesearch/Qwen3-30B-A3B-Base-alpaca-th-52k-dolly-th-15k-wangchan-instruct

sourceHugging Faceotherupdated 1y agoView on Hugging Face
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Qwen3-30B-A3B-Base-alpaca-th-52k-dolly-th-15k-wangchan-instruct

This model is a fine-tuned version of Qwen/Qwen3-30B-A3B-Base on the alpaca-th-52k, the dolly-th-15k and the wangchan-instruct datasets. It achieves the following results on the evaluation set:

  • —Loss: 0.6699

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: 0.0002
  • —trainbatchsize: 2
  • —evalbatchsize: 2
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 128
  • —gradientaccumulationsteps: 8
  • —totaltrainbatch_size: 2048
  • —totalevalbatch_size: 256
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 3.0

Training results

Training LossEpochStepValidation Loss
0.88650.2299101.0120
0.76980.4598200.8263
0.73760.6897300.7322
0.72020.9195400.7093
0.68261.1379500.6975
0.67181.3678600.6894
0.67261.5977700.6833
0.66831.8276800.6786
0.65322.0460900.6745
0.66222.27591000.6719
0.64762.50571100.6705
0.63992.73561200.6700
0.6432.96551300.6699

Framework versions

  • —PEFT 0.15.2
  • —Transformers 4.52.3
  • —Pytorch 2.7.0+cu126
  • —Datasets 3.6.0
  • —Tokenizers 0.21.1