---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  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. -->

# results

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: 0.7750
- Accuracy: 0.9257

## 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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 6.4334        | 1.0   | 593  | 6.1799          | 0.3660   |
| 4.3096        | 2.0   | 1186 | 3.9473          | 0.8412   |
| 2.6773        | 3.0   | 1779 | 2.3788          | 0.9079   |
| 1.7389        | 4.0   | 2372 | 1.5072          | 0.9197   |
| 1.1692        | 5.0   | 2965 | 1.0537          | 0.9236   |
| 0.9072        | 6.0   | 3558 | 0.8410          | 0.9254   |
| 0.7699        | 7.0   | 4151 | 0.7750          | 0.9257   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2