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--- |
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license: cc-by-sa-4.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fin |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: fin5 |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: fin |
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type: fin |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9243027888446215 |
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- name: Recall |
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type: recall |
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value: 0.9243027888446215 |
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- name: F1 |
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type: f1 |
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value: 0.9243027888446215 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9908666100254885 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# fin5 |
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This model is a fine-tuned version of [nlpaueb/sec-bert-shape](https://huggingface.co/nlpaueb/sec-bert-shape) on the fin dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0752 |
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- Precision: 0.9243 |
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- Recall: 0.9243 |
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- F1: 0.9243 |
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- Accuracy: 0.9909 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 129 | 0.0825 | 0.8327 | 0.8924 | 0.8615 | 0.9811 | |
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| No log | 2.0 | 258 | 0.0633 | 0.8593 | 0.9243 | 0.8906 | 0.9866 | |
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| No log | 3.0 | 387 | 0.0586 | 0.9038 | 0.9363 | 0.9198 | 0.9894 | |
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| 0.0547 | 4.0 | 516 | 0.0607 | 0.9357 | 0.9283 | 0.932 | 0.9911 | |
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| 0.0547 | 5.0 | 645 | 0.0656 | 0.9216 | 0.9363 | 0.9289 | 0.9904 | |
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| 0.0547 | 6.0 | 774 | 0.0692 | 0.9249 | 0.9323 | 0.9286 | 0.9909 | |
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| 0.0547 | 7.0 | 903 | 0.0716 | 0.9246 | 0.9283 | 0.9264 | 0.9904 | |
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| 0.0019 | 8.0 | 1032 | 0.0742 | 0.9213 | 0.9323 | 0.9267 | 0.9909 | |
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| 0.0019 | 9.0 | 1161 | 0.0748 | 0.9246 | 0.9283 | 0.9264 | 0.9909 | |
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| 0.0019 | 10.0 | 1290 | 0.0752 | 0.9243 | 0.9243 | 0.9243 | 0.9909 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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