---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: bert-keyword-extractor
  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. -->

# bert-keyword-extractor

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1341
- Precision: 0.8565
- Recall: 0.8874
- Accuracy: 0.9738
- F1: 0.8717

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:------:|
| 0.1688        | 1.0   | 1875  | 0.1233          | 0.7194    | 0.7738 | 0.9501   | 0.7456 |
| 0.1219        | 2.0   | 3750  | 0.1014          | 0.7724    | 0.8166 | 0.9606   | 0.7939 |
| 0.0834        | 3.0   | 5625  | 0.0977          | 0.8280    | 0.8263 | 0.9672   | 0.8272 |
| 0.0597        | 4.0   | 7500  | 0.0984          | 0.8304    | 0.8680 | 0.9704   | 0.8488 |
| 0.0419        | 5.0   | 9375  | 0.1042          | 0.8417    | 0.8687 | 0.9717   | 0.8550 |
| 0.0315        | 6.0   | 11250 | 0.1161          | 0.8520    | 0.8839 | 0.9729   | 0.8677 |
| 0.0229        | 7.0   | 13125 | 0.1282          | 0.8469    | 0.8939 | 0.9734   | 0.8698 |
| 0.0182        | 8.0   | 15000 | 0.1341          | 0.8565    | 0.8874 | 0.9738   | 0.8717 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1