phunganhsang / multi_task_model_content

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Model's Last Updated: November 07 2025

Introduction of multi_task_model_content

Model Details of multi_task_model_content

multi_task_model_content

This model is a fine-tuned version of RonTon05/model_content_V2_test on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9316
  • Accuracy: 0.6755
  • F1: 0.4286
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: 0.0001
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 10
Training results
Training Loss Epoch Step Validation Loss Accuracy F1
1.3757 1.0 330 1.2561 0.4734 0.1465
1.2316 2.0 660 1.1385 0.5831 0.2662
1.1559 3.0 990 1.0708 0.6375 0.3607
1.1027 4.0 1320 1.0156 0.6637 0.4096
1.0688 5.0 1650 0.9840 0.6608 0.4077
1.0474 6.0 1980 0.9621 0.6709 0.4164
1.0314 7.0 2310 0.9583 0.6645 0.4103
1.0212 8.0 2640 0.9407 0.6745 0.4258
1.0097 9.0 2970 0.9329 0.6758 0.4305
1.0096 10.0 3300 0.9316 0.6755 0.4286
Framework versions
  • Transformers 4.57.1
  • Pytorch 2.6.0+cu124
  • Datasets 4.4.1
  • Tokenizers 0.22.1

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https://huggingface.co/phunganhsang/multi_task_model_content

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https://huggingface.co/phunganhsang/multi_task_model_content

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phunganhsang
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Total runs: 2
Run Growth: 1
Growth Rate: 50.00%
Updated:October 06 2025