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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: 0.9666666666666667
- name: Accuracy
type: accuracy
value: 0.9375
---
<!-- 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: 0.2721
- F1: 0.9667
- Roc Auc: 0.9772
- Accuracy: 0.9375
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.7591 | 1.0 | 14 | 0.6660 | 0.3137 | 0.5541 | 0.0 |
| 0.6506 | 2.0 | 28 | 0.5575 | 0.4706 | 0.6451 | 0.0625 |
| 0.5006 | 3.0 | 42 | 0.5010 | 0.5385 | 0.6846 | 0.0625 |
| 0.4416 | 4.0 | 56 | 0.4536 | 0.6538 | 0.7528 | 0.125 |
| 0.3815 | 5.0 | 70 | 0.4127 | 0.8070 | 0.8589 | 0.5 |
| 0.3468 | 6.0 | 84 | 0.3748 | 0.8621 | 0.8984 | 0.5625 |
| 0.3316 | 7.0 | 98 | 0.3487 | 0.8621 | 0.8984 | 0.5625 |
| 0.2834 | 8.0 | 112 | 0.3191 | 0.9 | 0.9317 | 0.6875 |
| 0.2565 | 9.0 | 126 | 0.2970 | 0.9492 | 0.9606 | 0.875 |
| 0.2241 | 10.0 | 140 | 0.2721 | 0.9667 | 0.9772 | 0.9375 |
| 0.214 | 11.0 | 154 | 0.2563 | 0.9492 | 0.9606 | 0.875 |
| 0.2041 | 12.0 | 168 | 0.2499 | 0.9492 | 0.9606 | 0.875 |
| 0.1831 | 13.0 | 182 | 0.2353 | 0.9492 | 0.9606 | 0.875 |
| 0.1852 | 14.0 | 196 | 0.2285 | 0.9492 | 0.9606 | 0.875 |
| 0.1636 | 15.0 | 210 | 0.2178 | 0.9667 | 0.9772 | 0.9375 |
| 0.1581 | 16.0 | 224 | 0.2110 | 0.9667 | 0.9772 | 0.9375 |
| 0.1473 | 17.0 | 238 | 0.2057 | 0.9492 | 0.9606 | 0.875 |
| 0.1479 | 18.0 | 252 | 0.2025 | 0.9667 | 0.9772 | 0.9375 |
| 0.141 | 19.0 | 266 | 0.2038 | 0.9667 | 0.9772 | 0.9375 |
| 0.1424 | 20.0 | 280 | 0.2032 | 0.9667 | 0.9772 | 0.9375 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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