End of training
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README.md
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---
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license: cc-by-4.0
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base_model: NbAiLab/nb-bert-base
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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-base_FGN
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results: []
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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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# nb-bert-base_FGN
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This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0904
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- F1-score: 0.8074
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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: 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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### Training results
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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 | 0.6228 | 0.7307 |
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| No log | 2.0 | 240 | 0.7442 | 0.7474 |
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| No log | 3.0 | 360 | 0.7118 | 0.7785 |
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| No log | 4.0 | 480 | 1.2081 | 0.7137 |
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| 0.5388 | 5.0 | 600 | 1.1968 | 0.7628 |
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| 0.5388 | 6.0 | 720 | 1.0904 | 0.8074 |
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| 0.5388 | 7.0 | 840 | 1.2685 | 0.8007 |
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| 0.5388 | 8.0 | 960 | 1.4070 | 0.7783 |
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| 0.123 | 9.0 | 1080 | 1.6120 | 0.7608 |
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| 0.123 | 10.0 | 1200 | 1.5899 | 0.7695 |
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| 0.123 | 11.0 | 1320 | 1.4975 | 0.7705 |
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| 0.123 | 12.0 | 1440 | 1.4624 | 0.7983 |
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| 0.0475 | 13.0 | 1560 | 1.5148 | 0.7711 |
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| 0.0475 | 14.0 | 1680 | 1.4680 | 0.7926 |
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| 0.0475 | 15.0 | 1800 | 1.4216 | 0.8006 |
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| 0.0475 | 16.0 | 1920 | 1.4962 | 0.8006 |
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| 0.0201 | 17.0 | 2040 | 1.4150 | 0.7883 |
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| 0.0201 | 18.0 | 2160 | 1.4259 | 0.7755 |
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| 0.0201 | 19.0 | 2280 | 1.5040 | 0.7799 |
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| 0.0201 | 20.0 | 2400 | 1.5045 | 0.7808 |
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### Framework versions
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- Transformers 4.41.2
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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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model.safetensors
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