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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- filter_sort
metrics:
- f1
- accuracy
model-index:
- name: favs-filtersort-multilabel-classification-bert-base-cased
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: filter_sort
type: filter_sort
config: default
split: train
args: default
metrics:
- name: F1
type: f1
value: 0.7428571428571428
- name: Accuracy
type: accuracy
value: 0.2
---
<!-- 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-filtersort-multilabel-classification-bert-base-cased
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the filter_sort dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3066
- F1: 0.7429
- Roc Auc: 0.8142
- Accuracy: 0.2
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.7601 | 1.0 | 12 | 0.6966 | 0.2564 | 0.4518 | 0.0 |
| 0.6757 | 2.0 | 24 | 0.5629 | 0.6667 | 0.7785 | 0.0 |
| 0.5796 | 3.0 | 36 | 0.4652 | 0.6286 | 0.7477 | 0.0 |
| 0.5026 | 4.0 | 48 | 0.4161 | 0.6479 | 0.7605 | 0.0 |
| 0.4282 | 5.0 | 60 | 0.3830 | 0.6849 | 0.7862 | 0.0 |
| 0.4085 | 6.0 | 72 | 0.3658 | 0.7273 | 0.7962 | 0.0 |
| 0.3847 | 7.0 | 84 | 0.3538 | 0.7353 | 0.8052 | 0.0 |
| 0.3829 | 8.0 | 96 | 0.3457 | 0.6761 | 0.7772 | 0.0 |
| 0.3758 | 9.0 | 108 | 0.3409 | 0.6857 | 0.7810 | 0.0 |
| 0.3487 | 10.0 | 120 | 0.3327 | 0.7143 | 0.7976 | 0.0 |
| 0.3421 | 11.0 | 132 | 0.3268 | 0.6866 | 0.7758 | 0.0 |
| 0.3351 | 12.0 | 144 | 0.3183 | 0.7059 | 0.7886 | 0.0 |
| 0.3245 | 13.0 | 156 | 0.3149 | 0.7246 | 0.8014 | 0.0 |
| 0.3191 | 14.0 | 168 | 0.3087 | 0.7246 | 0.8014 | 0.1 |
| 0.3083 | 15.0 | 180 | 0.3066 | 0.7429 | 0.8142 | 0.2 |
| 0.3061 | 16.0 | 192 | 0.3062 | 0.7429 | 0.8142 | 0.2 |
| 0.2935 | 17.0 | 204 | 0.3017 | 0.7429 | 0.8142 | 0.2 |
| 0.2888 | 18.0 | 216 | 0.3009 | 0.7429 | 0.8142 | 0.2 |
| 0.297 | 19.0 | 228 | 0.3022 | 0.7429 | 0.8142 | 0.2 |
| 0.2868 | 20.0 | 240 | 0.3014 | 0.7429 | 0.8142 | 0.2 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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