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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: bertweet-base-finetuned-filtered-0609
    results: []

bertweet-base-finetuned-filtered-0609

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

  • Loss: 0.5397
  • Accuracy: 0.9299
  • Precision: 0.9297
  • Recall: 0.9299
  • F1: 0.9298

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: 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
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.331 1.0 3180 0.3687 0.9069 0.9147 0.9069 0.9081
0.2611 2.0 6360 0.3725 0.9223 0.9227 0.9223 0.9224
0.1993 3.0 9540 0.2948 0.9336 0.9350 0.9336 0.9339
0.1648 4.0 12720 0.3563 0.9296 0.9303 0.9296 0.9298
0.1324 5.0 15900 0.4136 0.9267 0.9279 0.9267 0.9270
0.1102 6.0 19080 0.4060 0.9352 0.9357 0.9352 0.9353
0.0568 7.0 22260 0.4653 0.9321 0.9328 0.9321 0.9322
0.0292 8.0 25440 0.4818 0.9311 0.9310 0.9311 0.9310
0.0155 9.0 28620 0.5405 0.9286 0.9288 0.9286 0.9286
0.0095 10.0 31800 0.5397 0.9299 0.9297 0.9299 0.9298

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.9.1+cu111
  • Datasets 1.16.1
  • Tokenizers 0.12.1