Hugging Face's logo

nguyenkhoa2407
/
favs-filtersort-multilabel-classification-bert-base-cased

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
1
favs-filtersort-multilabel-classification-bert-base-cased / README.md
nguyenkhoa2407's picture
nguyenkhoa2407
update model card README.md
6abe13c
preview code
|
raw
history blame
3.38 kB
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - filter_sort
metrics:
  - f1
  - accuracy
model-index:
  - name: favs-filtersort-multilabel-classification-bert-base-cased
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: filter_sort
          type: filter_sort
          config: default
          split: train
          args: default
        metrics:
          - name: F1
            type: f1
            value: 0.823529411764706
          - name: Accuracy
            type: accuracy
            value: 0

favs-filtersort-multilabel-classification-bert-base-cased

This model is a fine-tuned version of bert-base-cased on the filter_sort dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4283
  • F1: 0.8235
  • Roc Auc: 0.9058
  • Accuracy: 0.0

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: 1.5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
No log 1.0 9 0.5901 0.6087 0.7289 0.0
0.665 2.0 18 0.5667 0.4545 0.6201 0.0
0.6099 3.0 27 0.5573 0.5 0.6558 0.0
0.5463 4.0 36 0.5561 0.3889 0.5966 0.0
0.5071 5.0 45 0.5484 0.3889 0.5966 0.0
0.4669 6.0 54 0.5462 0.4324 0.6193 0.0
0.4371 7.0 63 0.5326 0.4737 0.6420 0.0
0.4145 8.0 72 0.5202 0.5854 0.7102 0.0
0.3959 9.0 81 0.5020 0.6364 0.7468 0.0
0.3733 10.0 90 0.4944 0.6364 0.7468 0.0
0.3733 11.0 99 0.4675 0.7234 0.8149 0.0
0.3622 12.0 108 0.4626 0.7843 0.8742 0.0
0.3382 13.0 117 0.4499 0.8077 0.8969 0.0
0.3341 14.0 126 0.4482 0.8077 0.8969 0.0
0.315 15.0 135 0.4332 0.8077 0.8969 0.0
0.3253 16.0 144 0.4283 0.8235 0.9058 0.0
0.3031 17.0 153 0.4246 0.8077 0.8969 0.0
0.3071 18.0 162 0.4155 0.8077 0.8969 0.0
0.2944 19.0 171 0.4129 0.8077 0.8969 0.0
0.2996 20.0 180 0.4129 0.8077 0.8969 0.0

Framework versions

  • Transformers 4.21.1
  • Pytorch 1.12.1
  • Datasets 2.4.0
  • Tokenizers 0.12.1