---
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert_base_cased
  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_cased

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5496
- Accuracy: 0.8505
- F1: 0.8971

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.6112        | 0.2174 | 50   | 0.6030          | 0.7328   | 0.8078 |
| 0.525         | 0.4348 | 100  | 0.4881          | 0.7525   | 0.8399 |
| 0.5386        | 0.6522 | 150  | 0.5263          | 0.7794   | 0.8544 |
| 0.4511        | 0.8696 | 200  | 0.5176          | 0.8137   | 0.875  |
| 0.2806        | 1.0870 | 250  | 0.4302          | 0.8088   | 0.8660 |
| 0.3622        | 1.3043 | 300  | 0.4826          | 0.8309   | 0.8816 |
| 0.2892        | 1.5217 | 350  | 0.3882          | 0.8358   | 0.8793 |
| 0.2732        | 1.7391 | 400  | 0.4186          | 0.8309   | 0.8856 |
| 0.3847        | 1.9565 | 450  | 0.3501          | 0.8431   | 0.8865 |
| 0.1997        | 2.1739 | 500  | 0.5521          | 0.8627   | 0.9060 |
| 0.162         | 2.3913 | 550  | 0.6342          | 0.8407   | 0.8926 |
| 0.1125        | 2.6087 | 600  | 0.5181          | 0.8578   | 0.9020 |
| 0.1388        | 2.8261 | 650  | 0.5496          | 0.8505   | 0.8971 |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2