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fin3
This model is a fine-tuned version of nlpaueb/sec-bert-base on the fin dataset. It achieves the following results on the evaluation set:
- Loss: 0.0748
- Precision: 0.944
- Recall: 0.9402
- F1: 0.9421
- Accuracy: 0.9921
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: 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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 129 | 0.0669 | 0.8821 | 0.9243 | 0.9027 | 0.9883 |
No log | 2.0 | 258 | 0.0568 | 0.9289 | 0.9363 | 0.9325 | 0.9913 |
No log | 3.0 | 387 | 0.0565 | 0.9141 | 0.9323 | 0.9231 | 0.9904 |
0.0556 | 4.0 | 516 | 0.0617 | 0.9237 | 0.9163 | 0.92 | 0.9904 |
0.0556 | 5.0 | 645 | 0.0658 | 0.9243 | 0.9243 | 0.9243 | 0.9904 |
0.0556 | 6.0 | 774 | 0.0695 | 0.944 | 0.9402 | 0.9421 | 0.9921 |
0.0556 | 7.0 | 903 | 0.0731 | 0.932 | 0.9283 | 0.9301 | 0.9917 |
0.0016 | 8.0 | 1032 | 0.0750 | 0.9283 | 0.9283 | 0.9283 | 0.9917 |
0.0016 | 9.0 | 1161 | 0.0737 | 0.944 | 0.9402 | 0.9421 | 0.9921 |
0.0016 | 10.0 | 1290 | 0.0748 | 0.944 | 0.9402 | 0.9421 | 0.9921 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2