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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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datasets: |
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- wnut_17 |
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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: my_awesome_wnut_model |
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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: wnut_17 |
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type: wnut_17 |
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config: wnut_17 |
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split: test |
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args: wnut_17 |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.55 |
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- name: Recall |
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type: recall |
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value: 0.37720111214087115 |
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- name: F1 |
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type: f1 |
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value: 0.44749862561847165 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9481063520560827 |
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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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# my_awesome_wnut_model |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wnut_17 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3958 |
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- Precision: 0.55 |
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- Recall: 0.3772 |
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- F1: 0.4475 |
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- Accuracy: 0.9481 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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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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| No log | 1.0 | 213 | 0.2562 | 0.5704 | 0.2929 | 0.3870 | 0.9417 | |
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| No log | 2.0 | 426 | 0.2776 | 0.5462 | 0.3179 | 0.4019 | 0.9436 | |
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| 0.1469 | 3.0 | 639 | 0.2834 | 0.5453 | 0.3624 | 0.4354 | 0.9475 | |
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| 0.1469 | 4.0 | 852 | 0.3004 | 0.5669 | 0.3652 | 0.4442 | 0.9480 | |
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| 0.0325 | 5.0 | 1065 | 0.3360 | 0.5858 | 0.3735 | 0.4561 | 0.9482 | |
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| 0.0325 | 6.0 | 1278 | 0.3471 | 0.5149 | 0.3855 | 0.4409 | 0.9474 | |
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| 0.0325 | 7.0 | 1491 | 0.3883 | 0.5552 | 0.3633 | 0.4392 | 0.9474 | |
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| 0.0117 | 8.0 | 1704 | 0.3881 | 0.5602 | 0.3707 | 0.4462 | 0.9477 | |
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| 0.0117 | 9.0 | 1917 | 0.4008 | 0.5582 | 0.3689 | 0.4442 | 0.9478 | |
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| 0.0051 | 10.0 | 2130 | 0.3958 | 0.55 | 0.3772 | 0.4475 | 0.9481 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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