---
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_08112024T144127
  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_08112024T144127

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: 0.4242
- F1: 0.8849
- 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   | 1.7911          | 0.1661 | 0.0000 |
| No log        | 2.0     | 173  | 1.6895          | 0.2558 | 0.0000 |
| No log        | 2.9942  | 259  | 1.5467          | 0.4336 | 0.0000 |
| No log        | 4.0     | 346  | 1.3716          | 0.5012 | 0.0000 |
| No log        | 4.9942  | 432  | 1.1818          | 0.5459 | 0.0000 |
| 1.5117        | 6.0     | 519  | 1.0336          | 0.5938 | 0.0000 |
| 1.5117        | 6.9942  | 605  | 0.9389          | 0.6309 | 1e-05  |
| 1.5117        | 8.0     | 692  | 0.8480          | 0.6802 | 0.0000 |
| 1.5117        | 8.9942  | 778  | 0.7481          | 0.7288 | 0.0000 |
| 1.5117        | 10.0    | 865  | 0.6824          | 0.7561 | 0.0000 |
| 1.5117        | 10.9942 | 951  | 0.6213          | 0.7867 | 0.0000 |
| 0.7682        | 12.0    | 1038 | 0.5781          | 0.8039 | 0.0000 |
| 0.7682        | 12.9942 | 1124 | 0.5184          | 0.8345 | 0.0000 |
| 0.7682        | 14.0    | 1211 | 0.4854          | 0.8489 | 0.0000 |
| 0.7682        | 14.9942 | 1297 | 0.4815          | 0.8559 | 0.0000 |
| 0.7682        | 16.0    | 1384 | 0.4422          | 0.8704 | 0.0000 |
| 0.7682        | 16.9942 | 1470 | 0.4422          | 0.8761 | 6e-06  |
| 0.305         | 18.0    | 1557 | 0.4368          | 0.8791 | 0.0000 |
| 0.305         | 18.9942 | 1643 | 0.4242          | 0.8849 | 0.0000 |
| 0.305         | 20.0    | 1730 | 0.4483          | 0.8829 | 0.0000 |
| 0.305         | 20.9942 | 1816 | 0.4539          | 0.8841 | 0.0000 |
| 0.305         | 22.0    | 1903 | 0.4521          | 0.8862 | 0.0000 |
| 0.305         | 22.9942 | 1989 | 0.4450          | 0.8896 | 0.0000 |
| 0.1014        | 24.0    | 2076 | 0.4603          | 0.8874 | 0.0000 |
| 0.1014        | 24.9942 | 2162 | 0.4750          | 0.8864 | 0.0000 |
| 0.1014        | 26.0    | 2249 | 0.4711          | 0.8887 | 7e-07  |
| 0.1014        | 26.9942 | 2335 | 0.4756          | 0.8879 | 4e-07  |
| 0.1014        | 28.0    | 2422 | 0.4691          | 0.8883 | 2e-07  |
| 0.0521        | 28.9942 | 2508 | 0.4694          | 0.8883 | 0.0    |
| 0.0521        | 29.8266 | 2580 | 0.4699          | 0.8883 | 0.0    |


### Framework versions

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