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Training complete
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README.md
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---
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license: apache-2.0
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base_model: bert-base-cased
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tags:
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- generated_from_trainer
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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: bert-finetuned-pos
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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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# bert-finetuned-pos
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1795
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- Precision: 0.9386
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- Recall: 0.9377
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- F1: 0.9382
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- Accuracy: 0.9579
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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: 3
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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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| 0.1872 | 1.0 | 1756 | 0.1998 | 0.9298 | 0.9300 | 0.9299 | 0.9520 |
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| 0.1247 | 2.0 | 3512 | 0.1837 | 0.9357 | 0.9334 | 0.9345 | 0.9557 |
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| 0.0913 | 3.0 | 5268 | 0.1795 | 0.9386 | 0.9377 | 0.9382 | 0.9579 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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runs/Apr16_08-40-07_b60ade9224d5/events.out.tfevents.1713256823.b60ade9224d5.5572.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:a39936eed77c3b0c9b76ac9e9c7338f9b39d5f4633cce27a0caafb4f9c1bf86a
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size 9905
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