---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: facility-classifier
  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. -->

# facility-classifier

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4422
- Accuracy: 0.7872
- F1: 0.7854

## 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.671         | 1.0   | 12   | 0.6529          | 0.6596   | 0.6441 |
| 0.5845        | 2.0   | 24   | 0.5722          | 0.7447   | 0.7461 |
| 0.4902        | 3.0   | 36   | 0.5091          | 0.7447   | 0.7461 |
| 0.378         | 4.0   | 48   | 0.4797          | 0.7660   | 0.7670 |
| 0.354         | 5.0   | 60   | 0.4487          | 0.8085   | 0.8029 |
| 0.2865        | 6.0   | 72   | 0.4422          | 0.7872   | 0.7854 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1