---
base_model: bert-base-uncased
library_name: peft
license: apache-2.0
metrics:
- f1
- accuracy
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: Bert-v1
  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-v1

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: 0.5738
- F1: 0.9637
- Accuracy: 0.9300
- Precision: 0.9302
- Recall: 0.9997

## 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: 0.002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
| 0.6498        | 0.0000 | 1    | 0.2875          | 0.9635 | 0.9295   | 0.9303    | 0.9991 |
| 0.2169        | 0.0000 | 2    | 0.2707          | 0.9635 | 0.9295   | 0.9303    | 0.9991 |
| 0.0354        | 0.0000 | 3    | 0.3281          | 0.9634 | 0.9294   | 0.9302    | 0.9991 |
| 0.0225        | 0.0000 | 4    | 0.3941          | 0.9635 | 0.9295   | 0.9302    | 0.9992 |
| 0.0021        | 0.0000 | 5    | 0.4481          | 0.9635 | 0.9295   | 0.9302    | 0.9992 |
| 0.0207        | 0.0000 | 6    | 0.4928          | 0.9635 | 0.9296   | 0.9302    | 0.9993 |
| 0.0131        | 0.0000 | 7    | 0.5282          | 0.9636 | 0.9298   | 0.9302    | 0.9995 |
| 0.0017        | 0.0001 | 8    | 0.5525          | 0.9637 | 0.9300   | 0.9302    | 0.9997 |
| 0.0002        | 0.0001 | 9    | 0.5672          | 0.9637 | 0.9300   | 0.9302    | 0.9997 |
| 0.0003        | 0.0001 | 10   | 0.5738          | 0.9637 | 0.9300   | 0.9302    | 0.9997 |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0