---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-large-csb
  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-large-csb

This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3276
- Accuracy: 0.8637
- F1: 0.8635

## 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: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4806        | 1.0   | 228  | 0.3276          | 0.8637   | 0.8635 |
| 0.3325        | 2.0   | 456  | 0.3070          | 0.8527   | 0.8530 |
| 0.2308        | 3.0   | 684  | 0.3310          | 0.8593   | 0.8585 |
| 0.1562        | 4.0   | 912  | 0.5863          | 0.8571   | 0.8547 |
| 0.1152        | 5.0   | 1140 | 0.7901          | 0.8462   | 0.8448 |
| 0.0424        | 6.0   | 1368 | 1.0230          | 0.8374   | 0.8342 |
| 0.018         | 7.0   | 1596 | 0.9910          | 0.8505   | 0.8499 |
| 0.0293        | 8.0   | 1824 | 1.1121          | 0.8484   | 0.8471 |
| 0.0075        | 9.0   | 2052 | 1.2002          | 0.8462   | 0.8446 |
| 0.0067        | 10.0  | 2280 | 1.1791          | 0.8440   | 0.8425 |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.2.1
- Datasets 4.4.1
- Tokenizers 0.22.1