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Acc0.9001248439450686, F10.8994770073289435 , Augmented with Synonym-wordnet.csv, finetuned on ProsusAI/finbert
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metadata
base_model: ProsusAI/finbert
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: finbert_Synonym-wordnet
    results: []

finbert_Synonym-wordnet

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

  • Loss: 0.2734
  • Accuracy: 0.9236
  • F1: 0.9232
  • Precision: 0.9236
  • Recall: 0.9236

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: 0.0001
  • train_batch_size: 64
  • eval_batch_size: 64
  • 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: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.7941 1.0 91 0.7038 0.7051 0.6964 0.7046 0.7051
0.3785 2.0 182 0.2841 0.8939 0.8940 0.8942 0.8939
0.213 3.0 273 0.2432 0.9080 0.9082 0.9106 0.9080
0.1268 4.0 364 0.3080 0.8924 0.8927 0.8956 0.8924
0.0851 5.0 455 0.2941 0.9173 0.9166 0.9183 0.9173
0.0797 6.0 546 0.2734 0.9236 0.9232 0.9236 0.9236
0.0651 7.0 637 0.3518 0.8970 0.8975 0.9029 0.8970
0.0779 8.0 728 0.4189 0.8939 0.8942 0.9016 0.8939
0.0923 9.0 819 0.3289 0.9126 0.9131 0.9152 0.9126
0.087 10.0 910 0.3797 0.9048 0.9047 0.9075 0.9048
0.0527 11.0 1001 0.3492 0.9048 0.9050 0.9058 0.9048

Framework versions

  • Transformers 4.37.0
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.1