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UIT-VSFC-Bert-CLSModel-v2

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bert
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UIT-VSFC-Bert-CLSModel-v2 / README.md
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metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: UIT-VSFC-Bert-CLSModel-v2
    results: []

UIT-VSFC-Bert-CLSModel-v2

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

  • Loss: 0.3111
  • Accuracy: 0.8970
  • F1: 0.6735
  • Precision: 0.8209
  • Recall: 0.6603

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: 128
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
No log 1.0 90 0.5202 0.8023 0.5646 0.7190 0.5744
No log 2.0 180 0.3222 0.8844 0.6687 0.7587 0.6550
No log 3.0 270 0.3111 0.8970 0.6735 0.8209 0.6603

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1