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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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- inspec |
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metrics: |
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- f1 |
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model-index: |
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- name: bert-finetuned-inspec |
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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: inspec |
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type: inspec |
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args: extraction |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.30353331752430635 |
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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-inspec |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the inspec dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3055 |
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- F1: 0.3035 |
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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: 5e-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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.3323 | 1.0 | 125 | 0.2799 | 0.1521 | |
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| 0.2563 | 2.0 | 250 | 0.2638 | 0.2230 | |
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| 0.2179 | 3.0 | 375 | 0.2689 | 0.2607 | |
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| 0.1809 | 4.0 | 500 | 0.2807 | 0.3122 | |
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| 0.1545 | 5.0 | 625 | 0.3055 | 0.3035 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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