---
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: 0.2580
- 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: 1.5e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.6752        | 1.0   | 13   | 0.6166          | 0.3810 | 0.5772  | 0.0      |
| 0.5905        | 2.0   | 26   | 0.5326          | 0.6286 | 0.7399  | 0.3636   |
| 0.5004        | 3.0   | 39   | 0.4812          | 0.5    | 0.6636  | 0.2727   |
| 0.4268        | 4.0   | 52   | 0.4346          | 0.7027 | 0.7899  | 0.4545   |
| 0.391         | 5.0   | 65   | 0.4072          | 0.8205 | 0.8737  | 0.5455   |
| 0.3725        | 6.0   | 78   | 0.3666          | 0.8108 | 0.8575  | 0.6364   |
| 0.3215        | 7.0   | 91   | 0.3382          | 0.8889 | 0.9     | 0.7273   |
| 0.3094        | 8.0   | 104  | 0.3083          | 0.9474 | 0.95    | 0.8182   |
| 0.2825        | 9.0   | 117  | 0.2925          | 0.9189 | 0.925   | 0.7273   |
| 0.2596        | 10.0  | 130  | 0.2801          | 0.9474 | 0.95    | 0.8182   |
| 0.2517        | 11.0  | 143  | 0.2580          | 1.0    | 1.0     | 1.0      |
| 0.2308        | 12.0  | 156  | 0.2538          | 0.9744 | 0.975   | 0.9091   |
| 0.238         | 13.0  | 169  | 0.2459          | 0.9744 | 0.975   | 0.9091   |
| 0.2194        | 14.0  | 182  | 0.2379          | 1.0    | 1.0     | 1.0      |
| 0.2181        | 15.0  | 195  | 0.2366          | 1.0    | 1.0     | 1.0      |


### Framework versions

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