tensorboard safetensors generated_from_trainer base_model:bert-base-uncased license:apache-2.0 region:us
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: whatsapp-group-classifierv3
  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. -->

# whatsapp-group-classifierv3

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4325
- Accuracy: 0.8454
- Precision: 0.8680
- Recall: 0.8522
- F1: 0.8589

## 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: 4e-05
- 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: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9598        | 1.0   | 513   | 0.6553          | 0.7366   | 0.7724    | 0.7280 | 0.7280 |
| 0.6517        | 2.0   | 1026  | 0.5718          | 0.7751   | 0.7888    | 0.7802 | 0.7817 |
| 0.5707        | 3.0   | 1539  | 0.5134          | 0.8024   | 0.8214    | 0.8059 | 0.8115 |
| 0.5246        | 4.0   | 2052  | 0.4874          | 0.8146   | 0.8376    | 0.8151 | 0.8243 |
| 0.4773        | 5.0   | 2565  | 0.4717          | 0.8215   | 0.8417    | 0.8295 | 0.8344 |
| 0.4512        | 6.0   | 3078  | 0.4586          | 0.8244   | 0.8465    | 0.8330 | 0.8389 |
| 0.4496        | 7.0   | 3591  | 0.4534          | 0.8332   | 0.8538    | 0.8380 | 0.8450 |
| 0.4164        | 8.0   | 4104  | 0.4432          | 0.8366   | 0.8615    | 0.8412 | 0.8501 |
| 0.4184        | 9.0   | 4617  | 0.4396          | 0.8356   | 0.8601    | 0.8407 | 0.8493 |
| 0.4075        | 10.0  | 5130  | 0.4346          | 0.8332   | 0.8563    | 0.8418 | 0.8480 |
| 0.3923        | 11.0  | 5643  | 0.4329          | 0.8395   | 0.8614    | 0.8453 | 0.8519 |
| 0.3886        | 12.0  | 6156  | 0.4367          | 0.8390   | 0.8623    | 0.8450 | 0.8525 |
| 0.3792        | 13.0  | 6669  | 0.4248          | 0.8390   | 0.8621    | 0.8431 | 0.8512 |
| 0.3659        | 14.0  | 7182  | 0.4252          | 0.84     | 0.8624    | 0.8483 | 0.8539 |
| 0.3738        | 15.0  | 7695  | 0.4236          | 0.8376   | 0.8606    | 0.8445 | 0.8515 |
| 0.3502        | 16.0  | 8208  | 0.4308          | 0.8444   | 0.8651    | 0.8521 | 0.8575 |
| 0.3574        | 17.0  | 8721  | 0.4292          | 0.8439   | 0.8658    | 0.8504 | 0.8572 |
| 0.3521        | 18.0  | 9234  | 0.4266          | 0.8449   | 0.8667    | 0.8512 | 0.8581 |
| 0.3306        | 19.0  | 9747  | 0.4247          | 0.8415   | 0.8666    | 0.8450 | 0.8543 |
| 0.3581        | 20.0  | 10260 | 0.4316          | 0.8449   | 0.8692    | 0.8531 | 0.8596 |
| 0.3223        | 21.0  | 10773 | 0.4342          | 0.8483   | 0.8713    | 0.8565 | 0.8624 |
| 0.3235        | 22.0  | 11286 | 0.4270          | 0.8473   | 0.8712    | 0.8551 | 0.8616 |
| 0.3281        | 23.0  | 11799 | 0.4263          | 0.8449   | 0.8686    | 0.8496 | 0.8579 |
| 0.313         | 24.0  | 12312 | 0.4319          | 0.8463   | 0.8677    | 0.8538 | 0.8598 |
| 0.32          | 25.0  | 12825 | 0.4305          | 0.8468   | 0.8681    | 0.8539 | 0.8600 |
| 0.3104        | 26.0  | 13338 | 0.4280          | 0.8488   | 0.8708    | 0.8543 | 0.8616 |
| 0.3203        | 27.0  | 13851 | 0.4309          | 0.8473   | 0.8698    | 0.8547 | 0.8611 |
| 0.304         | 28.0  | 14364 | 0.4298          | 0.8444   | 0.8671    | 0.8494 | 0.8572 |
| 0.3057        | 29.0  | 14877 | 0.4358          | 0.8498   | 0.8720    | 0.8575 | 0.8634 |
| 0.3238        | 30.0  | 15390 | 0.4325          | 0.8454   | 0.8680    | 0.8522 | 0.8589 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
