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End of training

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README.md ADDED
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+ ---
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+ license: cc-by-4.0
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+ base_model: NbAiLab/nb-bert-large
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: nb-bert-FGN
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+ results: []
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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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+ # nb-bert-FGN
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+
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+ This model is a fine-tuned version of [NbAiLab/nb-bert-large](https://huggingface.co/NbAiLab/nb-bert-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8455
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+ - F1-score: 0.8640
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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: 5e-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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1-score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 120 | 0.4694 | 0.8310 |
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+ | No log | 2.0 | 240 | 0.4810 | 0.8225 |
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+ | No log | 3.0 | 360 | 0.3942 | 0.8528 |
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+ | No log | 4.0 | 480 | 0.7082 | 0.7709 |
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+ | 0.4938 | 5.0 | 600 | 0.7041 | 0.8333 |
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+ | 0.4938 | 6.0 | 720 | 0.6616 | 0.8528 |
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+ | 0.4938 | 7.0 | 840 | 0.9447 | 0.8226 |
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+ | 0.4938 | 8.0 | 960 | 0.8971 | 0.8464 |
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+ | 0.2424 | 9.0 | 1080 | 0.9245 | 0.8348 |
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+ | 0.2424 | 10.0 | 1200 | 0.8455 | 0.8640 |
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+ | 0.2424 | 11.0 | 1320 | 0.8109 | 0.8571 |
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+ | 0.2424 | 12.0 | 1440 | 1.0194 | 0.8566 |
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+ | 0.1235 | 13.0 | 1560 | 0.9609 | 0.8533 |
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+ | 0.1235 | 14.0 | 1680 | 1.0777 | 0.8435 |
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+ | 0.1235 | 15.0 | 1800 | 1.1128 | 0.8450 |
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+ | 0.1235 | 16.0 | 1920 | 1.0391 | 0.8582 |
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+ | 0.0621 | 17.0 | 2040 | 1.1569 | 0.8507 |
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+ | 0.0621 | 18.0 | 2160 | 1.1449 | 0.8492 |
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+ | 0.0621 | 19.0 | 2280 | 1.1715 | 0.8492 |
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+ | 0.0621 | 20.0 | 2400 | 1.1702 | 0.8564 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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