subcate-ts / README.md
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subcate_ts
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metadata
license: mit
base_model: tangminhanh/cate-ts
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: subcate-ts
    results: []

subcate-ts

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

  • Loss: 0.0130
  • Accuracy: 0.3377
  • F1: 0.4963
  • Precision: 0.9460
  • Recall: 0.3364

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.8242 0.9987 188 0.2821 0.0 0.0081 0.0046 0.0321
0.1451 1.9973 376 0.0313 0.0 0.0 0.0 0.0
0.0298 2.9960 564 0.0231 0.0 0.0 0.0 0.0
0.024 4.0 753 0.0206 0.0 0.0 0.0 0.0
0.0212 4.9987 941 0.0181 0.1261 0.2233 0.9922 0.1258
0.0187 5.9973 1129 0.0162 0.2292 0.3696 0.9664 0.2285
0.0169 6.9960 1317 0.0147 0.3081 0.4657 0.9646 0.3070
0.0157 8.0 1506 0.0137 0.3184 0.4763 0.9551 0.3172
0.0151 8.9987 1694 0.0132 0.3310 0.4894 0.9486 0.3298
0.0145 9.9867 1880 0.0130 0.3377 0.4963 0.9460 0.3364

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1