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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: ChatGPT_Project |
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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: 0.36904761904761907 |
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- name: Recall |
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type: recall |
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value: 0.11492122335495829 |
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- name: F1 |
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type: f1 |
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value: 0.1752650176678445 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9319911088313243 |
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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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# ChatGPT_Project |
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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: 0.3070 |
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- Precision: 0.3690 |
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- Recall: 0.1149 |
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- F1: 0.1753 |
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- Accuracy: 0.9320 |
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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 | 0.4153 | 0.0 | 0.0 | 0.0 | 0.9256 | |
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| No log | 2.0 | 426 | 0.3484 | 0.0 | 0.0 | 0.0 | 0.9256 | |
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| 0.6399 | 3.0 | 639 | 0.3303 | 0.2222 | 0.0037 | 0.0073 | 0.9256 | |
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| 0.6399 | 4.0 | 852 | 0.3233 | 0.2179 | 0.0158 | 0.0294 | 0.9269 | |
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| 0.2004 | 5.0 | 1065 | 0.3164 | 0.3152 | 0.0482 | 0.0836 | 0.9286 | |
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| 0.2004 | 6.0 | 1278 | 0.3148 | 0.3421 | 0.0723 | 0.1194 | 0.9299 | |
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| 0.2004 | 7.0 | 1491 | 0.3100 | 0.3653 | 0.0918 | 0.1467 | 0.9309 | |
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| 0.1861 | 8.0 | 1704 | 0.3083 | 0.3522 | 0.0982 | 0.1536 | 0.9312 | |
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| 0.1861 | 9.0 | 1917 | 0.3057 | 0.3663 | 0.1168 | 0.1771 | 0.9320 | |
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| 0.1782 | 10.0 | 2130 | 0.3070 | 0.3690 | 0.1149 | 0.1753 | 0.9320 | |
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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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