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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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- precision |
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- recall |
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model-index: |
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- name: bert-finetuned-inspec-3-epochs |
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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: 0.28328008519701814 |
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- name: Precision |
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type: precision |
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value: 0.26594090202177295 |
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- name: Recall |
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type: recall |
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value: 0.3030379746835443 |
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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-3-epochs |
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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: 0.2728 |
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- F1: 0.2833 |
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- Precision: 0.2659 |
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- Recall: 0.3030 |
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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: 0 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:| |
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| 0.3338 | 1.0 | 125 | 0.2837 | 0.1401 | 0.1510 | 0.1306 | |
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| 0.2575 | 2.0 | 250 | 0.2658 | 0.2183 | 0.2519 | 0.1927 | |
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| 0.2259 | 3.0 | 375 | 0.2728 | 0.2833 | 0.2659 | 0.3030 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.1 |
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- Tokenizers 0.12.1 |
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