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---
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
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