---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert_test_8
  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_test_8

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: 0.7390
- F1: 0.8624

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.5054        | 1.0   | 341  | 0.8553          | 0.7042 |
| 0.7004        | 2.0   | 682  | 0.5741          | 0.8367 |
| 0.4056        | 3.0   | 1023 | 0.4853          | 0.8504 |
| 0.2813        | 4.0   | 1364 | 0.4766          | 0.8574 |
| 0.1813        | 5.0   | 1705 | 0.4964          | 0.8536 |
| 0.1327        | 6.0   | 2046 | 0.5343          | 0.8648 |
| 0.1148        | 7.0   | 2387 | 0.6017          | 0.8723 |
| 0.0755        | 8.0   | 2728 | 0.6251          | 0.8684 |
| 0.0552        | 9.0   | 3069 | 0.6666          | 0.8624 |
| 0.0442        | 10.0  | 3410 | 0.6992          | 0.8670 |
| 0.0308        | 11.0  | 3751 | 0.7045          | 0.8705 |
| 0.0235        | 12.0  | 4092 | 0.7237          | 0.8607 |
| 0.0219        | 13.0  | 4433 | 0.7377          | 0.8596 |
| 0.0249        | 14.0  | 4774 | 0.7384          | 0.8646 |
| 0.0214        | 15.0  | 5115 | 0.7390          | 0.8624 |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3