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---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: distilbert-finetuned-headings
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-finetuned-headings
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1669
- F1 Positive: 0.9112
- F1 Negative: 0.9854
- F1: 0.9749
- Roc Auc: 0.9457
- Accuracy: 0.9749
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Positive | F1 Negative | F1 | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:-----------:|:------:|:-------:|:--------:|
| 0.1869 | 1.0 | 1785 | 0.1452 | 0.8621 | 0.9793 | 0.9640 | 0.8922 | 0.9640 |
| 0.1306 | 2.0 | 3570 | 0.1190 | 0.8738 | 0.9807 | 0.9665 | 0.9031 | 0.9665 |
| 0.1182 | 3.0 | 5355 | 0.1460 | 0.8831 | 0.9818 | 0.9685 | 0.9137 | 0.9685 |
| 0.0841 | 4.0 | 7140 | 0.1431 | 0.8990 | 0.9844 | 0.9730 | 0.9201 | 0.9730 |
| 0.061 | 5.0 | 8925 | 0.1540 | 0.9066 | 0.9846 | 0.9736 | 0.9431 | 0.9736 |
| 0.0381 | 6.0 | 10710 | 0.1630 | 0.9070 | 0.9851 | 0.9743 | 0.9359 | 0.9743 |
| 0.0268 | 7.0 | 12495 | 0.1669 | 0.9112 | 0.9854 | 0.9749 | 0.9457 | 0.9749 |
| 0.024 | 8.0 | 14280 | 0.2216 | 0.8964 | 0.9827 | 0.9704 | 0.9412 | 0.9704 |
| 0.0182 | 9.0 | 16065 | 0.2294 | 0.9032 | 0.9843 | 0.9730 | 0.9371 | 0.9730 |
| 0.0176 | 10.0 | 17850 | 0.2239 | 0.9057 | 0.9847 | 0.9736 | 0.9393 | 0.9736 |
| 0.0197 | 11.0 | 19635 | 0.2441 | 0.8966 | 0.9832 | 0.9710 | 0.9340 | 0.9710 |
| 0.0128 | 12.0 | 21420 | 0.2541 | 0.8899 | 0.9820 | 0.9691 | 0.9310 | 0.9691 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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