---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- filter_v2
metrics:
- f1
- accuracy
model-index:
- name: favs_filter_classification_v2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: filter_v2
      type: filter_v2
      config: default
      split: train
      args: default
    metrics:
    - name: F1
      type: f1
      value: 1.0
    - name: Accuracy
      type: accuracy
      value: 1.0
---

<!-- 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_filter_classification_v2

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the filter_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2201
- F1: 1.0
- Roc Auc: 1.0
- Accuracy: 1.0

## 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: 1.3e-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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.6747        | 1.0   | 13   | 0.5868          | 0.5    | 0.6649  | 0.1818   |
| 0.5843        | 2.0   | 26   | 0.5321          | 0.4828 | 0.6575  | 0.0      |
| 0.5445        | 3.0   | 39   | 0.5029          | 0.6    | 0.7162  | 0.2727   |
| 0.4713        | 4.0   | 52   | 0.4667          | 0.6207 | 0.725   | 0.2727   |
| 0.4304        | 5.0   | 65   | 0.4321          | 0.6667 | 0.7575  | 0.4545   |
| 0.3983        | 6.0   | 78   | 0.3909          | 0.7500 | 0.8     | 0.4545   |
| 0.3433        | 7.0   | 91   | 0.3571          | 0.7879 | 0.825   | 0.5455   |
| 0.3186        | 8.0   | 104  | 0.3319          | 0.8235 | 0.85    | 0.6364   |
| 0.2967        | 9.0   | 117  | 0.3049          | 0.8571 | 0.875   | 0.6364   |
| 0.2739        | 10.0  | 130  | 0.2857          | 0.8571 | 0.875   | 0.6364   |
| 0.2535        | 11.0  | 143  | 0.2686          | 0.9474 | 0.95    | 0.8182   |
| 0.234         | 12.0  | 156  | 0.2501          | 0.9474 | 0.95    | 0.8182   |
| 0.2338        | 13.0  | 169  | 0.2358          | 0.9474 | 0.95    | 0.8182   |
| 0.2049        | 14.0  | 182  | 0.2201          | 1.0    | 1.0     | 1.0      |
| 0.1942        | 15.0  | 195  | 0.2098          | 1.0    | 1.0     | 1.0      |
| 0.1957        | 16.0  | 208  | 0.2063          | 1.0    | 1.0     | 1.0      |
| 0.1892        | 17.0  | 221  | 0.1969          | 1.0    | 1.0     | 1.0      |
| 0.1836        | 18.0  | 234  | 0.1919          | 1.0    | 1.0     | 1.0      |
| 0.1767        | 19.0  | 247  | 0.1909          | 1.0    | 1.0     | 1.0      |
| 0.1702        | 20.0  | 260  | 0.1901          | 1.0    | 1.0     | 1.0      |


### Framework versions

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