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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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+ - xglue
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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-tiny-finetuned-xglue-ner
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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: xglue
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+ type: xglue
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+ config: ner
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+ split: train
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+ args: ner
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.630759453447728
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+ - name: Recall
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+ type: recall
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+ value: 0.6681252103668799
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+ - name: F1
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+ type: f1
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+ value: 0.6489048708728343
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9274310133922189
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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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+ # bert-tiny-finetuned-xglue-ner
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+
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+ This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the xglue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2489
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+ - Precision: 0.6308
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+ - Recall: 0.6681
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+ - F1: 0.6489
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+ - Accuracy: 0.9274
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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: 3
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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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+ | 0.4082 | 1.0 | 1756 | 0.3326 | 0.5600 | 0.5798 | 0.5697 | 0.9118 |
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+ | 0.2974 | 2.0 | 3512 | 0.2635 | 0.6143 | 0.6562 | 0.6346 | 0.9248 |
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+ | 0.2741 | 3.0 | 5268 | 0.2489 | 0.6308 | 0.6681 | 0.6489 | 0.9274 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.21.0
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+ - Pytorch 1.12.0+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1