---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: results
  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. -->

# results

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: 0.2919
- Precision: 0.8957
- Recall: 0.8226
- F1: 0.8576

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.3611        | 0.2   | 500  | 0.3194          | 0.8640    | 0.8324 | 0.8479 |
| 0.3106        | 0.4   | 1000 | 0.3039          | 0.8905    | 0.8013 | 0.8435 |
| 0.3027        | 0.6   | 1500 | 0.2954          | 0.9022    | 0.7927 | 0.8439 |
| 0.2952        | 0.81  | 2000 | 0.2864          | 0.8966    | 0.8185 | 0.8558 |
| 0.2905        | 1.01  | 2500 | 0.2875          | 0.8973    | 0.8150 | 0.8542 |
| 0.2605        | 1.21  | 3000 | 0.2841          | 0.8924    | 0.8369 | 0.8637 |
| 0.2591        | 1.41  | 3500 | 0.2820          | 0.8926    | 0.8444 | 0.8678 |
| 0.2574        | 1.61  | 4000 | 0.2826          | 0.8916    | 0.8359 | 0.8629 |
| 0.2602        | 1.81  | 4500 | 0.2764          | 0.8989    | 0.8291 | 0.8626 |
| 0.2561        | 2.01  | 5000 | 0.2813          | 0.8891    | 0.8454 | 0.8667 |
| 0.2195        | 2.22  | 5500 | 0.2869          | 0.9072    | 0.8110 | 0.8564 |
| 0.2209        | 2.42  | 6000 | 0.2845          | 0.9002    | 0.8216 | 0.8591 |
| 0.2178        | 2.62  | 6500 | 0.2827          | 0.8991    | 0.8285 | 0.8624 |
| 0.22          | 2.82  | 7000 | 0.2919          | 0.8957    | 0.8226 | 0.8576 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2