---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-base-uncased_12112024T103207
  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-base-uncased_12112024T103207

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4280
- F1: 0.8755
- Learning Rate: 0.0

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 600
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | F1     | Rate   |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| No log        | 0.9942  | 86   | 1.7552          | 0.1858 | 0.0000 |
| No log        | 2.0     | 173  | 1.6269          | 0.3187 | 0.0000 |
| No log        | 2.9942  | 259  | 1.4885          | 0.4438 | 0.0000 |
| No log        | 4.0     | 346  | 1.3478          | 0.4980 | 0.0000 |
| No log        | 4.9942  | 432  | 1.1903          | 0.5445 | 0.0000 |
| 1.5065        | 6.0     | 519  | 1.0219          | 0.5810 | 0.0000 |
| 1.5065        | 6.9942  | 605  | 0.9065          | 0.6140 | 1e-05  |
| 1.5065        | 8.0     | 692  | 0.7955          | 0.6526 | 0.0000 |
| 1.5065        | 8.9942  | 778  | 0.6876          | 0.7032 | 0.0000 |
| 1.5065        | 10.0    | 865  | 0.6171          | 0.7536 | 0.0000 |
| 1.5065        | 10.9942 | 951  | 0.5734          | 0.7612 | 0.0000 |
| 0.7171        | 12.0    | 1038 | 0.4960          | 0.8147 | 0.0000 |
| 0.7171        | 12.9942 | 1124 | 0.4820          | 0.8358 | 0.0000 |
| 0.7171        | 14.0    | 1211 | 0.4557          | 0.8445 | 0.0000 |
| 0.7171        | 14.9942 | 1297 | 0.4596          | 0.8524 | 0.0000 |
| 0.7171        | 16.0    | 1384 | 0.4299          | 0.8651 | 0.0000 |
| 0.7171        | 16.9942 | 1470 | 0.4426          | 0.8671 | 6e-06  |
| 0.2382        | 18.0    | 1557 | 0.4280          | 0.8755 | 0.0000 |
| 0.2382        | 18.9942 | 1643 | 0.4517          | 0.8728 | 0.0000 |
| 0.2382        | 20.0    | 1730 | 0.4473          | 0.8761 | 0.0000 |
| 0.2382        | 20.9942 | 1816 | 0.4599          | 0.8798 | 0.0000 |
| 0.2382        | 22.0    | 1903 | 0.4927          | 0.8777 | 0.0000 |
| 0.2382        | 22.9942 | 1989 | 0.4768          | 0.8819 | 0.0000 |
| 0.0713        | 24.0    | 2076 | 0.4970          | 0.8808 | 0.0000 |
| 0.0713        | 24.9942 | 2162 | 0.5031          | 0.8808 | 0.0000 |
| 0.0713        | 26.0    | 2249 | 0.4807          | 0.8845 | 7e-07  |
| 0.0713        | 26.9942 | 2335 | 0.4959          | 0.8825 | 4e-07  |
| 0.0713        | 28.0    | 2422 | 0.5034          | 0.8818 | 2e-07  |
| 0.0344        | 28.9942 | 2508 | 0.5037          | 0.8818 | 0.0    |
| 0.0344        | 29.8266 | 2580 | 0.5037          | 0.8824 | 0.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1