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update model card README.md

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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: fin4
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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: 0.9209486166007905
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+ - name: Recall
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+ type: recall
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+ value: 0.9282868525896414
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+ - name: F1
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+ type: f1
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+ value: 0.9246031746031745
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9913080347678609
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+ ---
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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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+
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+ # fin4
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+
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+ This model is a fine-tuned version of [nlpaueb/sec-bert-num](https://huggingface.co/nlpaueb/sec-bert-num) on the fin dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0549
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+ - Precision: 0.9209
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+ - Recall: 0.9283
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+ - F1: 0.9246
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+ - Accuracy: 0.9913
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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 | 0.1041 | 0.8242 | 0.8406 | 0.8323 | 0.9788 |
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+ | No log | 2.0 | 258 | 0.0511 | 0.9173 | 0.9283 | 0.9228 | 0.9902 |
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+ | No log | 3.0 | 387 | 0.0430 | 0.9102 | 0.9283 | 0.9191 | 0.9907 |
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+ | 0.0598 | 4.0 | 516 | 0.0501 | 0.9368 | 0.9442 | 0.9405 | 0.9922 |
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+ | 0.0598 | 5.0 | 645 | 0.0436 | 0.9325 | 0.9363 | 0.9344 | 0.9924 |
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+ | 0.0598 | 6.0 | 774 | 0.0489 | 0.9433 | 0.9283 | 0.9357 | 0.9917 |
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+ | 0.0598 | 7.0 | 903 | 0.0499 | 0.932 | 0.9283 | 0.9301 | 0.9919 |
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+ | 0.0028 | 8.0 | 1032 | 0.0537 | 0.9209 | 0.9283 | 0.9246 | 0.9913 |
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+ | 0.0028 | 9.0 | 1161 | 0.0540 | 0.9170 | 0.9243 | 0.9206 | 0.9911 |
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+ | 0.0028 | 10.0 | 1290 | 0.0549 | 0.9209 | 0.9283 | 0.9246 | 0.9913 |
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+
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+
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+ ### Framework versions
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+
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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