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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: 0.9761904761904762
- name: Accuracy
type: accuracy
value: 0.9545454545454546
---
<!-- 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: 0.2016
- F1: 0.9762
- Roc Auc: 0.9844
- Accuracy: 0.9545
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.6596 | 1.0 | 16 | 0.6086 | 0.2687 | 0.5474 | 0.0 |
| 0.5448 | 2.0 | 32 | 0.5354 | 0.3824 | 0.6063 | 0.0 |
| 0.5106 | 3.0 | 48 | 0.4874 | 0.4444 | 0.6382 | 0.0455 |
| 0.4353 | 4.0 | 64 | 0.4301 | 0.5352 | 0.6889 | 0.1818 |
| 0.3699 | 5.0 | 80 | 0.3890 | 0.6579 | 0.7640 | 0.3636 |
| 0.349 | 6.0 | 96 | 0.3663 | 0.6667 | 0.7633 | 0.3182 |
| 0.3104 | 7.0 | 112 | 0.3327 | 0.7105 | 0.7953 | 0.4545 |
| 0.3023 | 8.0 | 128 | 0.2971 | 0.7733 | 0.8303 | 0.5455 |
| 0.2676 | 9.0 | 144 | 0.2766 | 0.8395 | 0.8861 | 0.7727 |
| 0.2374 | 10.0 | 160 | 0.2541 | 0.8537 | 0.8980 | 0.7727 |
| 0.2238 | 11.0 | 176 | 0.2399 | 0.9024 | 0.9293 | 0.8182 |
| 0.2084 | 12.0 | 192 | 0.2221 | 0.9286 | 0.9531 | 0.8636 |
| 0.2143 | 13.0 | 208 | 0.2138 | 0.9286 | 0.9531 | 0.8636 |
| 0.1846 | 14.0 | 224 | 0.2016 | 0.9762 | 0.9844 | 0.9545 |
| 0.1812 | 15.0 | 240 | 0.1957 | 0.9762 | 0.9844 | 0.9545 |
| 0.1756 | 16.0 | 256 | 0.1881 | 0.9647 | 0.9806 | 0.9091 |
| 0.1662 | 17.0 | 272 | 0.1845 | 0.9762 | 0.9844 | 0.9545 |
| 0.1715 | 18.0 | 288 | 0.1802 | 0.9762 | 0.9844 | 0.9545 |
| 0.1585 | 19.0 | 304 | 0.1782 | 0.9762 | 0.9844 | 0.9545 |
| 0.1595 | 20.0 | 320 | 0.1775 | 0.9762 | 0.9844 | 0.9545 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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