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--- |
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license: apache-2.0 |
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base_model: distilbert-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: distilbert-finetuned-headings |
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results: [] |
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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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# distilbert-finetuned-headings |
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This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1669 |
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- F1 Positive: 0.9112 |
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- F1 Negative: 0.9854 |
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- F1: 0.9749 |
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- Roc Auc: 0.9457 |
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- Accuracy: 0.9749 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 32 |
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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: 12 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Positive | F1 Negative | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:-----------:|:------:|:-------:|:--------:| |
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| 0.1869 | 1.0 | 1785 | 0.1452 | 0.8621 | 0.9793 | 0.9640 | 0.8922 | 0.9640 | |
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| 0.1306 | 2.0 | 3570 | 0.1190 | 0.8738 | 0.9807 | 0.9665 | 0.9031 | 0.9665 | |
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| 0.1182 | 3.0 | 5355 | 0.1460 | 0.8831 | 0.9818 | 0.9685 | 0.9137 | 0.9685 | |
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| 0.0841 | 4.0 | 7140 | 0.1431 | 0.8990 | 0.9844 | 0.9730 | 0.9201 | 0.9730 | |
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| 0.061 | 5.0 | 8925 | 0.1540 | 0.9066 | 0.9846 | 0.9736 | 0.9431 | 0.9736 | |
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| 0.0381 | 6.0 | 10710 | 0.1630 | 0.9070 | 0.9851 | 0.9743 | 0.9359 | 0.9743 | |
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| 0.0268 | 7.0 | 12495 | 0.1669 | 0.9112 | 0.9854 | 0.9749 | 0.9457 | 0.9749 | |
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| 0.024 | 8.0 | 14280 | 0.2216 | 0.8964 | 0.9827 | 0.9704 | 0.9412 | 0.9704 | |
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| 0.0182 | 9.0 | 16065 | 0.2294 | 0.9032 | 0.9843 | 0.9730 | 0.9371 | 0.9730 | |
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| 0.0176 | 10.0 | 17850 | 0.2239 | 0.9057 | 0.9847 | 0.9736 | 0.9393 | 0.9736 | |
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| 0.0197 | 11.0 | 19635 | 0.2441 | 0.8966 | 0.9832 | 0.9710 | 0.9340 | 0.9710 | |
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| 0.0128 | 12.0 | 21420 | 0.2541 | 0.8899 | 0.9820 | 0.9691 | 0.9310 | 0.9691 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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