---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- filter_sort
metrics:
- f1
- accuracy
model-index:
- name: favs-filtersort-multilabel-classification-bert-base-cased
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: filter_sort
      type: filter_sort
      config: default
      split: train
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.7428571428571428
    - name: Accuracy
      type: accuracy
      value: 0.2
---

<!-- 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. -->

# favs-filtersort-multilabel-classification-bert-base-cased

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the filter_sort dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3066
- F1: 0.7429
- Roc Auc: 0.8142
- Accuracy: 0.2

## 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: 1.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.7601        | 1.0   | 12   | 0.6966          | 0.2564 | 0.4518  | 0.0      |
| 0.6757        | 2.0   | 24   | 0.5629          | 0.6667 | 0.7785  | 0.0      |
| 0.5796        | 3.0   | 36   | 0.4652          | 0.6286 | 0.7477  | 0.0      |
| 0.5026        | 4.0   | 48   | 0.4161          | 0.6479 | 0.7605  | 0.0      |
| 0.4282        | 5.0   | 60   | 0.3830          | 0.6849 | 0.7862  | 0.0      |
| 0.4085        | 6.0   | 72   | 0.3658          | 0.7273 | 0.7962  | 0.0      |
| 0.3847        | 7.0   | 84   | 0.3538          | 0.7353 | 0.8052  | 0.0      |
| 0.3829        | 8.0   | 96   | 0.3457          | 0.6761 | 0.7772  | 0.0      |
| 0.3758        | 9.0   | 108  | 0.3409          | 0.6857 | 0.7810  | 0.0      |
| 0.3487        | 10.0  | 120  | 0.3327          | 0.7143 | 0.7976  | 0.0      |
| 0.3421        | 11.0  | 132  | 0.3268          | 0.6866 | 0.7758  | 0.0      |
| 0.3351        | 12.0  | 144  | 0.3183          | 0.7059 | 0.7886  | 0.0      |
| 0.3245        | 13.0  | 156  | 0.3149          | 0.7246 | 0.8014  | 0.0      |
| 0.3191        | 14.0  | 168  | 0.3087          | 0.7246 | 0.8014  | 0.1      |
| 0.3083        | 15.0  | 180  | 0.3066          | 0.7429 | 0.8142  | 0.2      |
| 0.3061        | 16.0  | 192  | 0.3062          | 0.7429 | 0.8142  | 0.2      |
| 0.2935        | 17.0  | 204  | 0.3017          | 0.7429 | 0.8142  | 0.2      |
| 0.2888        | 18.0  | 216  | 0.3009          | 0.7429 | 0.8142  | 0.2      |
| 0.297         | 19.0  | 228  | 0.3022          | 0.7429 | 0.8142  | 0.2      |
| 0.2868        | 20.0  | 240  | 0.3014          | 0.7429 | 0.8142  | 0.2      |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1