---
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: 0.7714285714285716
    - name: Accuracy
      type: accuracy
      value: 0.4
---

<!-- 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: 0.2711
- F1: 0.7714
- Roc Auc: 0.8309
- Accuracy: 0.4

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.6535        | 1.0   | 12   | 0.5860          | 0.4524 | 0.6444  | 0.0      |
| 0.5843        | 2.0   | 24   | 0.5121          | 0.5    | 0.6708  | 0.0      |
| 0.5308        | 3.0   | 36   | 0.4460          | 0.5484 | 0.6950  | 0.0      |
| 0.4663        | 4.0   | 48   | 0.4023          | 0.5574 | 0.6989  | 0.0      |
| 0.4116        | 5.0   | 60   | 0.3769          | 0.5806 | 0.7117  | 0.0      |
| 0.3936        | 6.0   | 72   | 0.3620          | 0.6032 | 0.7245  | 0.0      |
| 0.3691        | 7.0   | 84   | 0.3519          | 0.625  | 0.7373  | 0.0      |
| 0.3565        | 8.0   | 96   | 0.3410          | 0.6269 | 0.7425  | 0.0      |
| 0.3548        | 9.0   | 108  | 0.3324          | 0.6562 | 0.7540  | 0.0      |
| 0.3235        | 10.0  | 120  | 0.3229          | 0.6866 | 0.7758  | 0.1      |
| 0.3157        | 11.0  | 132  | 0.3115          | 0.7164 | 0.7924  | 0.2      |
| 0.297         | 12.0  | 144  | 0.3055          | 0.7164 | 0.7924  | 0.2      |
| 0.2923        | 13.0  | 156  | 0.2988          | 0.7246 | 0.8014  | 0.2      |
| 0.2848        | 14.0  | 168  | 0.2903          | 0.7164 | 0.7924  | 0.2      |
| 0.2715        | 15.0  | 180  | 0.2908          | 0.7429 | 0.8142  | 0.3      |
| 0.2696        | 16.0  | 192  | 0.2807          | 0.7353 | 0.8052  | 0.3      |
| 0.2543        | 17.0  | 204  | 0.2794          | 0.7536 | 0.8181  | 0.3      |
| 0.2504        | 18.0  | 216  | 0.2711          | 0.7714 | 0.8309  | 0.4      |
| 0.2577        | 19.0  | 228  | 0.2708          | 0.7536 | 0.8181  | 0.3      |
| 0.2401        | 20.0  | 240  | 0.2693          | 0.7536 | 0.8181  | 0.3      |
| 0.2415        | 21.0  | 252  | 0.2669          | 0.7714 | 0.8309  | 0.4      |
| 0.241         | 22.0  | 264  | 0.2691          | 0.7536 | 0.8181  | 0.3      |
| 0.2341        | 23.0  | 276  | 0.2669          | 0.7536 | 0.8181  | 0.3      |
| 0.2355        | 24.0  | 288  | 0.2660          | 0.7536 | 0.8181  | 0.3      |
| 0.232         | 25.0  | 300  | 0.2655          | 0.7536 | 0.8181  | 0.3      |


### Framework versions

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