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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- udpos28
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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: udpos28-sm-first-POS
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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: udpos28
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type: udpos28
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args: en
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metrics:
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- name: Precision
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type: precision
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value: 0.9511089206505667
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- name: Recall
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type: recall
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value: 0.9546093116207286
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- name: F1
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type: f1
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value: 0.9528559014062253
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- name: Accuracy
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type: accuracy
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value: 0.9559133601686793
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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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# udpos28-sm-first-POS
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the udpos28 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1896
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- Precision: 0.9511
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- Recall: 0.9546
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- F1: 0.9529
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- Accuracy: 0.9559
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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: 4
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- eval_batch_size: 4
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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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- lr_scheduler_warmup_ratio: 0.1
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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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| 0.1696 | 1.0 | 4978 | 0.1700 | 0.9440 | 0.9464 | 0.9452 | 0.9472 |
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| 0.0973 | 2.0 | 9956 | 0.1705 | 0.9487 | 0.9533 | 0.9510 | 0.9543 |
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| 0.0508 | 3.0 | 14934 | 0.1896 | 0.9511 | 0.9546 | 0.9529 | 0.9559 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.10.2+cu102
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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