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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: finbert-finetuned-FG-SINGLE_SENTENCE-NEWS
    results: []

finbert-finetuned-FG-SINGLE_SENTENCE-NEWS

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

  • Loss: 3.2997
  • Accuracy: 0.6414
  • F1: 0.6295

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: 6e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • 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 Accuracy F1
No log 1.0 321 0.9371 0.5699 0.4333
0.9282 2.0 642 0.9135 0.5930 0.5447
0.9282 3.0 963 0.9900 0.6033 0.5823
0.6743 4.0 1284 1.0802 0.6142 0.6065
0.3134 5.0 1605 1.5156 0.6183 0.5971
0.3134 6.0 1926 1.3695 0.6319 0.6183
0.1709 7.0 2247 1.8746 0.6462 0.6267
0.1112 8.0 2568 2.0880 0.6176 0.6155
0.1112 9.0 2889 2.3953 0.6190 0.6087
0.0811 10.0 3210 2.3792 0.6339 0.6225
0.0608 11.0 3531 2.3783 0.6360 0.6282
0.0608 12.0 3852 2.5982 0.6544 0.6351
0.039 13.0 4173 2.7687 0.6346 0.6305
0.039 14.0 4494 2.8980 0.6414 0.6299
0.0206 15.0 4815 3.0858 0.6319 0.6253
0.0168 16.0 5136 3.2408 0.6244 0.6170
0.0168 17.0 5457 3.1809 0.6435 0.6293
0.0123 18.0 5778 3.2629 0.6449 0.6324
0.0055 19.0 6099 3.2866 0.6449 0.6308
0.0055 20.0 6420 3.2997 0.6414 0.6295

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.9.1
  • Datasets 1.18.4
  • Tokenizers 0.11.6