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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- arxiv_dataset |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: baseline_BERT_50K_steps |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: arxiv_dataset |
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type: arxiv_dataset |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9936787420400056 |
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- name: Precision |
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type: precision |
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value: 0.7967781908302355 |
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- name: Recall |
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type: recall |
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value: 0.4734468476760239 |
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- name: F1 |
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type: f1 |
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value: 0.5939610876970152 |
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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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# baseline_BERT_50K_steps |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the arxiv_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0192 |
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- Accuracy: 0.9937 |
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- Precision: 0.7968 |
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- Recall: 0.4734 |
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- F1: 0.5940 |
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- Hamming: 0.0063 |
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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: 6 |
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- eval_batch_size: 6 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 50000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Hamming | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
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| 0.0343 | 0.03 | 10000 | 0.0315 | 0.9912 | 0.7679 | 0.1370 | 0.2326 | 0.0088 | |
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| 0.0244 | 0.06 | 20000 | 0.0234 | 0.9925 | 0.7813 | 0.3262 | 0.4602 | 0.0075 | |
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| 0.0219 | 0.09 | 30000 | 0.0210 | 0.9931 | 0.7572 | 0.4320 | 0.5502 | 0.0069 | |
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| 0.0204 | 0.12 | 40000 | 0.0197 | 0.9935 | 0.7738 | 0.4711 | 0.5857 | 0.0065 | |
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| 0.0197 | 0.15 | 50000 | 0.0192 | 0.9937 | 0.7968 | 0.4734 | 0.5940 | 0.0063 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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