---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-finetuned-sla
  results: []
---

<!-- 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. -->

# bert-finetuned-sla

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3317
- F1: 0.6207
- Roc Auc: 0.7439
- Accuracy: 0.4902

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 30   | 0.4847          | 0.1795 | 0.5463  | 0.1176   |
| No log        | 2.0   | 60   | 0.4364          | 0.3956 | 0.6237  | 0.2549   |
| No log        | 3.0   | 90   | 0.3896          | 0.4176 | 0.6328  | 0.2941   |
| No log        | 4.0   | 120  | 0.3633          | 0.5818 | 0.7180  | 0.4314   |
| No log        | 5.0   | 150  | 0.3497          | 0.6271 | 0.7496  | 0.4706   |
| No log        | 6.0   | 180  | 0.3317          | 0.6207 | 0.7439  | 0.4902   |
| No log        | 7.0   | 210  | 0.3300          | 0.6271 | 0.7496  | 0.4706   |
| No log        | 8.0   | 240  | 0.3191          | 0.6218 | 0.7478  | 0.4706   |
| No log        | 9.0   | 270  | 0.3223          | 0.6271 | 0.7496  | 0.4706   |
| No log        | 10.0  | 300  | 0.3189          | 0.6325 | 0.7513  | 0.4706   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2